Transfer Learning for Visual Categorization: A Survey

Distinctive Image Features from Scale-Invariant Keypoints

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Histograms of Oriented Gradients for Human Detection

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The Elements of Statistical Learning

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A survey on transfer learning

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Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries

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Hmdb: a large video database for human motion recognition

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Learning realistic human actions from movies

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Mangrove semantic segmentation on aerial images

Arias-Aguilar, J. A., López-Jiménez, E., Ramírez-Cárdenas, O. D., Lozada, J. C. H., & Montiel, N. H. (2024) · IEEE Latin America Transactions · doi:10.1109/tla.2024.10500718 · Cited by 4

ER-GMMD: Cross-Scene Remote Sensing Classification Method of Tamarix chinensis in the Yellow River Estuary

Zhu, L., Hu, Y., Ren, G., Qiao, N., Meng, Z., Wang, J., Zhao, Y., Li, S., & Ma, Y. (2025) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2024.3523346 · Cited by 4

Transfer learning approach to modeling multichannel gate-all-around nanosheet field-effect transistors under work function fluctuations

Dash, S., & Li, Y. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.110322 · Cited by 4

Boosted Cross-Domain Categorization

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Smoke detection in a digital image with the use of convolutional network

Jakubowski, J., Solarczyk, M., & Wiśnios, M. (2019) · Conference on Reconnaissance and Electronic Warfare Systems (CREWS) · doi:10.1117/12.2524560 · Cited by 4

Impact of data smoothing on semantic segmentation

Haq, N. U., Rehman, Z. U., Khan, A., Din, A., Shah, S., Ullah, A., & Qayum, F. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-05341-4 · Cited by 4

A Study on Image Analysis and Recognition Using Learning Methods: CNN as the Best Image Learner

Vidushi, & Agarwal, M. (2021) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-15-8335-3_3 · Cited by 4

Diversity-promoting multi-view graph learning for semi-supervised classification

Zhan, S., Sun, W., Du, C., & Zhong, W. (2021) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-021-01370-0 · Cited by 4

Transfer Learning in Brain Tumor Detection: from AlexNet to Hyb-DCNN-ResNet

Kuang, Z. (2022) · Highlights in Science Engineering and Technology · doi:10.54097/hset.v4i.919 · Cited by 4

An Introduction to Federated and Transfer Learning

Razavi‐Far, R., Wang, B., Taylor, M. E., & Yang, Q. (2022) · Adaptation, learning, and optimization · doi:10.1007/978-3-031-11748-0_1 · Cited by 4

A Priori Quantification of Transfer Learning Performance on Time Series Classification for Cyber-Physical Health Systems

Clark, R., & Doyle, T. E. (2022) · Conference proceedings - Canadian Conference on Electrical and Computer Engineering · doi:10.1109/ccece49351.2022.9918279 · Cited by 4

A Transfer Learning Algorithm Based on Support Vector Machine

Wu, W., Chen, S., & Bao, L. (2022) · Neural Processing Letters · doi:10.1007/s11063-022-11126-8 · Cited by 4

A Method of Reliability Assessment Based on Fine Tuning Deep Learning Model for Open Source Software in Edge Computing

Tamura, Y., & Yamada, S. (2023) · International Journal of Reliability Quality and Safety Engineering · doi:10.1142/s0218539323500109 · Cited by 4

Image‐Based Flow Regime Recognition in Aerated Stirred Tanks Using Deep Transfer Learning

Khaydarov, V., Becker, M., & Urbas, L. (2023) · Chemie Ingenieur Technik · doi:10.1002/cite.202200246 · Cited by 4

Open set text recognition technology

Yang, C. H., Liu, C., Fang, Z., Han, Z., Liu, C., & Yin, X.-C. (2023) · Journal of Image and Graphics · doi:10.11834/jig.230018 · Cited by 4

Transfer Learning for the Choquet Integral

Murray, B., Islam, M. A., Pinar, A. J., Anderson, D. T., Scott, G. J., Havens, T. C., Petry, F. E., & Elmore, P. (2019) · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) · doi:10.1109/fuzz-ieee.2019.8858844 · Cited by 4

A progressive learning framework based on single-instance annotation for weakly supervised object detection

Zhang, M., & Zeng, B. (2020) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2020.102903 · Cited by 4

Variant transfer learning for wood recognition

Huang, P., Zhao, F., Li, X., ZhangKang, W., Zhu, Z., & Zhang, Y. (2020) · IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) · doi:10.1109/ithings-greencom-cpscom-smartdata-cybermatics50389.2020.00128 · Cited by 4

An Attention Enhanced Cross-Modal Image–Sound Mutual Generation Model for Birds

Hao, W., Han, M., Li, S., & Li, F. (2020) · The Computer Journal · doi:10.1093/comjnl/bxaa188 · Cited by 4

Semantic class discriminant projection for image retrieval with relevance feedback

Huu, Q. N., Viet, D. C., & Thuy, Q. D. T. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-020-10400-y · Cited by 4

Edge AI for Industry 4.0: An Internet of Things Approach

Tziouvaras, A., & Foukalas, F. T. (2020) · Panhellenic Conference on Informatics · doi:10.1145/3437120.3437289 · Cited by 5

Transfer Learning-Based Intelligent Diagnosis for Skin Lesion in Cloud-Edge Computing Networks

Gu, M., Li, X., & Chen, S. (2021) · International Conference on Wireless Communications and Signal Processing (WCSP) · doi:10.1109/wcsp52459.2021.9613544 · Cited by 4

An Identification Method of Apple Leaf Disease Based on Transfer Learning

Su, J., Zhang, M., & Yu, W. (2022) · International Conference on Cloud Computing and Big Data Analytics (ICCCBDA) · doi:10.1109/icccbda55098.2022.9778876 · Cited by 4

Ground Pedestrian and Vehicle Detections Using Imaging Environment Perception Mechanisms and Deep Learning Networks

Liu, H., Chen, S., Zheng, N. E., Wang, Y., Ge, J., Ding, K., Guo, Z., Li, W., & Lan, J. (2022) · Electronics · doi:10.3390/electronics11121873 · Cited by 4

Bicycle Detection Based On Multi-feature and Multi-frame Fusion in low-resolution traffic videosPreprint

Zhang, Y., & Qiang, L. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1706.03309 · Cited by 4

Hiding in the deep : online animal activity recognition using motion sensors and machine learning

Kamminga, J. W. (2020) · doi:10.3990/1.9789036550550 · Cited by 4

A Distributed Multifactorial Particle Swarm Optimization ApproachPreprint

Aboud, A., Rokbani, N., Mirjalili, S., Qahtani, A. M., Almutiry, O., Dhahri, H., & Alimi, A. M. (2021) · doi:10.36227/techrxiv.17260040.v1 · Cited by 4

Synergy of Edge Intelligence and Blockchain: A Comprehensive SurveyPreprint

Wang, X., Ren, X., Qiu, C., Xiong, Z., Yao, H., & Leung, V. C. M. (2021) · doi:10.36227/techrxiv.14724360 · Cited by 4

Postural Classification by Image Embedding and Transfer Learning: An Example of Using the OWAS Method in Motor-Manual Work to Automate the Process and Save Resources

Forkuo, G. O., Borz, S. A., Kaakkurivaara, T., & Kaakkurivaara, N. (2025) · Forests · doi:10.3390/f16030492 · Cited by 3

Entropy calibrated prototype embedding for transductive few-shot learning

Guo, M., Wang, J., Xu, Q., Jiang, B., & Luo, B. (2026) · Pattern Recognition Letters · doi:10.1016/j.patrec.2026.01.015 · Cited by 3

Acousto-optic-driven detection of underwater surface defects in reservoir dams: A review and prospect

Zhaohan, L. I. U., & Su, H. (2026) · Measurement · doi:10.1016/j.measurement.2026.120417 · Cited by 3

A Systematic Review of Transfer Learning Research From the Perspective of Knowledge Graph: Visual Analysis Based on the Bibliometric Method

An, Y., Hou, N., & Lv, Z. (2026) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.70084 · Cited by 3

QNet: A Quick Deep Neural Network for Real-Time Semantic Segmentation

Xia, A., Li, D., Cai, J., Gu, H., & Qin, P. (2020) · IEEE International Conference on Signal and Image Processing (ICSIP) · doi:10.1109/icsip49896.2020.9339426 · Cited by 3

A Novel Approach to Image Colorization Algorithm using Convolutional Neural Networks

Singla, M., Jain, A., Mantri, M., Tulshain, S., Muthu, R. K., & Naidu, R. C. (2022) · International Conference on Applied Artificial Intelligence and Computing (ICAAIC) · doi:10.1109/icaaic53929.2022.9793234 · Cited by 3

IDCIA: Immunocytochemistry Dataset for Cellular Image Analysis

Mohammed, A. A., Fonder, C., Sakaguchi, D. S., Tavanapong, W., Mallapragada, S. K., & Idris, A. (2023) · ACM Multimedia Systems Conference (MMSys) · doi:10.1145/3587819.3592558 · Cited by 3

Phase retrieval for X-ray differential phase contrast radiography with knowledge transfer learning from virtual differential absorption model

Tao, S., Tian, Z., Bai, L., Xu, Y., Kuang, C., & Liu, X. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107711 · Cited by 3

On the Treatment of Measurement Errors for Magnetic Angular Sensors With Neural Networks

Meier, P., Rohrmann, K., Sandner, M., Prochaska, M., & Ferhi, O. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3342824 · Cited by 3

Generating Synthetic MR Spectroscopic Imaging Data with Generative Adversarial Networks to Train Machine Learning Models

Maruyama, S., & Takeshima, H. (2024) · Magnetic Resonance in Medical Sciences · doi:10.2463/mrms.mp.2023-0125 · Cited by 3

Relative Performance Prediction Using Few-Shot Learning

Dey, A., Dhakal, A. R., Islam, T. Z., Yeom, J.-S., Patki, T., Nichols, D., Movsesyan, A., & Bhatele, A. S. (2024) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac61105.2024.00278 · Cited by 3

Generating High-Quality Datasets With Critical State Samples for Data-Driven Power System Applications

Zhang, Z., Bai, X., Weng, Z., Xiao, J., & Zhang, J. (2025) · IEEE Access · doi:10.1109/access.2025.3539787 · Cited by 3

Prediction Method for Carbon Emission of Hobbing Based on Cross-Process Data Fusion

Yi, Q., Luo, Y., Hu, C., Li, C., & Yi, S. (2025) · Chinese Journal of Mechanical Engineering · doi:10.1186/s10033-025-01192-z · Cited by 3

May the torcher light our way: A negative-accelerated active learning framework for image classification

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Distributed and Context Aware Application of Deep Neural Networks in Mobile 3D-Multi-sensor Systems Based on Cloud-, Edge- and FPGA-Computing

Engel, G., Bhatti, F., Greiner, T., Heizmann, M., & Quint, F. (2020) · IEEE International Conference on Industrial Engineering and Applications (ICIEA) · doi:10.1109/iciea49774.2020.9101915 · Cited by 3

Communication Specific Emitter Identification Based on Transfer Learning

Liu, H., Hu, P., & Liu, Z. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1626/1/012027 · Cited by 3

Investigating the optimisation of real-world and synthetic object detection training datasets through the consideration of environmental and simulation factors

Newman, C., Petzing, J. N., Goh, Y. M., & Justham, L. (2022) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2022.200079 · Cited by 3

Smart Image Storage and Retrieval For Crime Scene Investigation

Rane, D., Shinde, B., Vaity, S., & Shingane, P. (2022) · International Conference on Emerging Trends in Engineering and Technology (ICETET) · doi:10.1109/icetet-sip-2254415.2022.9791537 · Cited by 3

Application of deep learning methods: From molecular modelling to patient classification

Fu, X., & Bates, P. A. (2022) · Experimental Cell Research · doi:10.1016/j.yexcr.2022.113278 · Cited by 3

Shared Dictionary Learning Via Coupled Adaptations for Cross-Domain Classification

Cai, Y., Li, J., Liu, B., Cao, W., Chen, H., & Liu, W. (2022) · Neural Processing Letters · doi:10.1007/s11063-022-10967-7 · Cited by 3

Bearing Fault Diagnosis Method Based on Transfer Ensemble Learning

Luo, P., Yin, Z., Zhang, Y., Yuan, D., & Yang, H. (2022) · IEEE International Electrical and Energy Conference (CIEEC) · doi:10.1109/cieec54735.2022.9846015 · Cited by 3

Effective Reinforcement Learning using Transfer Learning

Varma, N. S., Pradyumna Rahul, K., & Sinha, V. (2022) · International Conference on Data Science and Information System (ICDSIS) · doi:10.1109/icdsis55133.2022.9915962 · Cited by 3

Integrated Intelligent Surveillance System Using Deep Learning

Paul, A., Paul, S., R, M. A., Jose, K. P., & Sabarinath, M. S. (2023) · International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS) · doi:10.1109/access57397.2023.10200245 · Cited by 3

Homogeneous transfer learning for supporting pervasive edge applications

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A concise review towards a novel target specific multi-source unsupervised transfer learning technique for GDP estimation using CO2 emission data

Kumar, S., & Muhuri, P. K. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10858-4 · Cited by 3

Graph-based semisupervised and manifold learning for image retrieval with SVM-based relevant feedback

Huu, Q. N., Viet, D. C., Thuy, Q. D. T., Quoc, T. N., & Van, C. P. (2019) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-181237 · Cited by 3

Quality Image Enhancement from Low Resolution Camera using Convolutional Neural Network

Patmawati, N. P., Arifianto, A., & Ramadhani, K. N. (2019) · doi:10.1109/icoict.2019.8835273 · Cited by 3

A Novel Algorithm for Efficient Labeling and Its Application to On-Road Risk Detection

Hu, Y., Zhao, Q., & Tomioka, Y. (2019) · IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) · doi:10.1109/dasc/picom/cbdcom/cyberscitech.2019.00141 · Cited by 3

Active learning for image preparation of automatic vending machine (AVM) employing transfer learning method

Li, F., Zeng, M., Xiao, J., Li, X., Li, Y., & Hu, G. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1684/1/012114 · Cited by 3

Multi-source domain adaptation-based low-rank representation and correlation alignment

Madadi, Y., Seydi, V., & Hosseini, R. (2021) · International Journal of Computers and Applications · doi:10.1080/1206212x.2021.1885786 · Cited by 3

Workflow on CNN utilization and inference in FPGA for embedded applications: 6th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM 2021)

Flamis, G., Kalapothas, S., & Kitsos, P. (2021) · South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM) · doi:10.1109/seeda-cecnsm53056.2021.9566259 · Cited by 3

Artificial Intelligence Framework for Content-Based Image Retrieval: Performance Analysis

Desai, P., & Pujari, J. (2022) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-16-9113-3_39 · Cited by 3

Classifying Economic Areas for Urban Planning using Deep Learning and Satellite Imagery in East Africa

Uwizera, D. K., Ruranga, C., & McSharry, P. (2022) · SAIEE Africa Research Journal · doi:10.23919/saiee.2022.9945864 · Cited by 3

Brain Tumor Detection Using Advanced Deep Learning Implementations

Shrotriya, L., Agarwal, G., Mishra, K., Mishra, S., Bidwe, R. V., & Kaur, G. (2023) · Traitement du signal · doi:10.18280/ts.400508 · Cited by 3

A Transfer Learning and Performance Comparison of Deep Learning Models for Pedestrian Classification under Automobile Driving Environment

Byeon, Y.-H., & Kwak, K.-C. (2018) · The Journal of Korean Institute of Information Technology · doi:10.14801/jkiit.2018.16.10.83 · Cited by 3

Conditional Adaptation Deep Networks for Unsupervised Cross Domain Image Classifcation

Chen, Y., Yang, C., Zhang, Y., & Li, Y. (2019) · IEEE Conference on Industrial Electronics and Applications (ICIEA) · doi:10.1109/iciea.2019.8834368 · Cited by 3

A low computational approach for price tag recognition

Aliev, M., Nikolaev, D., Kunina, I., & Bocharov, D. (2020) · International Conference on Machine Vision · doi:10.1117/12.2557618 · Cited by 3

Multiple-source Domain Adaptation in Rule-based Neural Network

Zuo, H., Jie Lu, B., & Zhang, G. (2020) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn48605.2020.9206761 · Cited by 3

Plastic Gasket Defect Detection Based on Transfer Learning

Chen, X., Wang, D., Shao, J., & Fan, J. (2021) · Scientific Programming · doi:10.1155/2021/5990020 · Cited by 3

From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks

Roder, M., Almeida, J., de Rosa, G. H., Júnior, L. A. P., Rossi, A. L. D., & Papa, J. P. (2021) · IEEE Symposium Series on Computational Intelligence (SSCI) · doi:10.1109/ssci50451.2021.9660128 · Cited by 3

State identification of transfer learning based Yolov4 network for isolation switches used in substations

Huang, X., Tang, B., Zhu, M., Shen, L., Ma, Y., Wang, X., Zhang, Z., & Xiao, D. (2022) · Frontiers in Energy Research · doi:10.3389/fenrg.2022.1000459 · Cited by 3

A Novel Convolutional Neural Network Based on Combined Features from Different Transformations for Brain Tumor Diagnosis

El-Wahab, B. S. A., NASR, M. E. M., Khamis, S., & Ashour, A. S. (2023) · Journal of Engineering Research - Egypt/Journal of Engineering Research · doi:10.21608/erjeng.2023.217931.1188 · Cited by 3

Diet and Health Advisory Mechanism from Facial Features Using Machine Learning

Chheda, T., Bhinderwala, H., Acharya, P., & Nimkar, A. V. (2019) · doi:10.1109/icit48102.2019.00051 · Cited by 3

A new intelligent retail container system with a dual neural network model design

Zeng, M., Wu, S., Li, F., & Hu, G. (2020) · International Conference on Computer Engineering and Intelligent Control (ICCEIC) · doi:10.1109/icceic51584.2020.00025 · Cited by 3

Synergy of Edge Intelligence and Blockchain: A Comprehensive SurveyPreprint

Wang, X., Ren, X., Qiu, C., Xiong, Z., Yao, H., & Leung, V. C. M. (2021) · doi:10.36227/techrxiv.14724360.v1 · Cited by 3

Multimodal Biometric in Computer Vision

Shivthare, S. K., Sharma, Y. K., & Patil, R. D. (2023) · Wiley eBooks · doi:10.1002/9781119785491.ch1 · Cited by 3

Diagnosing, Classifying, and Predicting Brain Tumors from MRI Images Using VGG-19 and ANN Transfer LearningPreprint

Jamshidi, B., & Rostamy‐Malkhalifeh, M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4624936 · Cited by 3

A Time-frequency Signal-based Convolutional Neural Network Algorithm for Fault Diagnosis of Gasoline Engine Fuel Control System

Lin, S.-C., Su, S., & Huang, Y. (2019) · International Conference on System Science and Engineering · doi:10.1109/icsse.2019.8823285 · Cited by 2

An improved open-view human action recognition with unsupervised domain adaptation

Samsudin, M. S. R., Abu–Bakar, S. A. R., & Mokji, M. M. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-12822-2 · Cited by 2

Blood Sample Image Classification Algorithm Based on SVM and HOG

Jiang, T., Ying, S., Fang, Z., Xue, S., Sun, Y., Zhan, D., & Ma, C. (2022) · Journal of New Media · doi:10.32604/jnm.2022.027175 · Cited by 2

Transductive Few-shot Learning via Joint Message Passing and Prototype-based Soft-label Propagation

Wang, J., Xu, Q., Jiang, B., & Luo, B. (2025) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3719204 · Cited by 3

Multimodal Artificial Intelligence Using Endoscopic USG, CT, and MRI to Differentiate Between Serous and Mucinous Cystic Neoplasms

Seza, K., Tawada, K., Kobayashi, A., & Nakamura, K. (2025) · Cureus · doi:10.7759/cureus.85547 · Cited by 2

An effective detection algorithm for small UAV based on lightweight You-Only-Look-Once (YOLOv4-L) approach

Li, G., Cheng, J., Liu, Y., Li, J., Lv, Z., & Li, Q. (2025) · Applied Soft Computing · doi:10.1016/j.asoc.2025.113841 · Cited by 2

Map wisely for efficient transfer learning across heterogeneous data sources

Acharya, S., & Das, M. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.131762 · Cited by 2

A metaheuristic-driven deep feature selection approach for hyperspectral image classification

Raina, S., & Kaul, A. (2026) · Remote Sensing Applications Society and Environment · doi:10.1016/j.rsase.2026.101916 · Cited by 2

A Few-Shot Wind Turbine Blade Surface Faults Detection via Enhanced Data Augmentation and Progressive Transfer Learning

Fang, F., Tang, L., Nian, J., Wei, L., & Wu, X. (2026) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2026.3664590 · Cited by 3

A Physics-Informed Topology-Adaptive Graph Convolutional Network for Harmonic Source Location in Three-Phase Distribution Networks With Renewable Energy Integration

Zhou, L., Shao, Z., Chen, F., Cheng, G., Lin, C., Chen, Z., & Zheng, Z. (2026) · IEEE Transactions on Power Delivery · doi:10.1109/tpwrd.2026.3680264 · Cited by 2

Unraveling hidden species diversity of talpid moles using phylogenomics and skull-based deep learning

He, K., Li, A., Martinez, Q., Wang, X., Chen, Z., He, S., Xie, S., Zeng, Z., Wang, K., Ye, Z., et al. (2026) · Communications Biology · doi:10.1038/s42003-026-10392-9 · Cited by 2

Transfer Learning on Fine-Grained Categorization

Firsching, J., & Hashem, S. R. (2020) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-63128-4_43 · Cited by 2

Facial Expression Recognition to Aid Visually Impaired People

Silva, J. M., Silva, R., Veras, R. D. M. S., Aires, K. R. T., & Neto, L. D. S. B. (2021) · Workshop de Visão Computacional (WVC) · doi:10.5753/wvc.2021.18888 · Cited by 2

Intrusion detection algorithom based on transfer extreme learning machine

Wang, K., Li, J., & Wu, W. (2023) · Intelligent Data Analysis · doi:10.3233/ida-216475 · Cited by 2

YOLO-IP

Nayak, R., Dwivedi, P., & Pati, U. C. (2023) · Practice, progress, and proficiency in sustainability · doi:10.4018/978-1-6684-8516-3.ch008 · Cited by 2

Transfer Learning for Computer Vision

Khan, Q. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-1738-9.ch002 · Cited by 2

Detection of Brain Tumour in MRI Images using Deep Belief Network (DBN)

Jahan, R., & Tripathi, M. M. (2024) · Journal of Advanced Research in Applied Sciences and Engineering Technology · doi:10.37934/araset.41.1.154167 · Cited by 3

Unsupervised Domain Adaptation Remote Sensing Image Classification Based on Class Centroid Alignment

Wang, F., Liang, Y., Cui, Y., Li, S., & Wang, R. (2023) · China Automation Congress (CAC) · doi:10.1109/cac59555.2023.10451399 · Cited by 2

Boosting Methods Comparison : XGBoost, Adaboost and Gradient Boosting for Business Partner Performance Prediction

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A Transfer Learning Radiomics Nomogram to Predict the Postoperative Recurrence of Advanced Gastric Cancer

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