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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A decision-theoretic generalization of on-line learning and an application to boosting

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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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Mixture of Deep-Based Representation and Shallow Classifiers to Recognize Human Activities

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Developing Brain Tumor Detection Model Using Deep Feature Extraction via Transfer Learning

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A Comparative Study of Image Classification Models for Western Notation to Carnatic Notation : Conversion of Western Music Notation to Carnatic Music Notation

Prathyushaa, V. K., Chandrasekar, P. S., & Anuradha, R. (2021) · International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · doi:10.1109/i-smac52330.2021.9641052 · Cited by 2

Convolutional Neural Network Training System For Eye Location On Infrared Driver Recordings Using Automatically Generated Ground Truth Data

Valcan, S. (2021) · International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) · doi:10.1109/synasc54541.2021.00045 · Cited by 2

Unsupervised domain adaptation via transferred local Fisher discriminant analysis

Zandifar, M., Rezaei, S., & Tahmoresnezhad, J. (2023) · Iran Journal of Computer Science · doi:10.1007/s42044-023-00144-x · Cited by 2

Optical Based Gradient-Weighted Class Activation Mapping and Transfer Learning Integrated Pneumonia Prediction Model

Jan, C.-W., Chiu, Y.-J., Chen, K.-L., Yao, T.-C., & Kuo, P. (2023) · Computer Systems Science and Engineering · doi:10.32604/csse.2023.042078 · Cited by 2

Impact of Trivial Solutions on Classification Tasks Using CNNs

Fromme, D., Kaupenjohann, M., & Thiem, J. (2023) · IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) · doi:10.1109/idaacs58523.2023.10348715 · Cited by 2

Heterogeneous domain adaptation by class centroid matching and local discriminative structure preservation

Chen, Y., Zhou, H., Wang, Z., & Zhong, P. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-09786-9 · Cited by 2

Enhanced Brain Tumor Analysis: Integrating ResNet50 with Convolutional Block Attention Modules for Advanced Insights

Vinston Raja, R. (2024) · Journal of Electrical Systems · doi:10.52783/jes.3272 · Cited by 4

Embracing Domain Gradient Conflicts: Domain Generalization Using Domain Gradient Equilibrium

Zhang, Z., Li, Y., & Shin, B. (2024) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3664647.3681141 · Cited by 2

Transformer-based identification for ADS-B transmitters in open–time sets

Zheng, Y., Zhang, X., Tan, Y., & Li, X. (2025) · Chinese Journal of Aeronautics · doi:10.1016/j.cja.2025.103418 · Cited by 2

An inverter nonlinearity identification method based on physics-informed network for different working conditions

Lu, J., Sun, W., Jiang, D. L., Li, D., & Qu, R. (2025) · Electrical Engineering · doi:10.1007/s00202-025-02981-4 · Cited by 2

Transferring Knowledge from Observed to Unknown: A Data-Driven Lane Change Trajectory Prediction Strategy Based on the Concept of Few-Shot Learning

Zhao, N., Lu, Y., Wang, B., Cheng, X., Luo, R., Song, Y., Zhou, Y., & Su, R. (2024) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc58415.2024.10920270 · Cited by 2

Heterogeneous Feature Space Based Task Selection Machine for Unsupervised Transfer Learning

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Transfer learning in neural networks: an experience report

Shtern, M., Ejaz, R., & Tzerpos, V. (2017) · Computer Science and Software Engineering · Cited by 2

Automated Ultrasound Doppler Angle Estimation Using Deep Learning

Patil, N., & Anand, A. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8857587 · Cited by 2

Sample-oriented Domain Adaptation for Image Classification

Zandifar, M., & Tahmoresnezhad, J. (2019) · Signal and Data Processing · doi:10.29252/jsdp.16.3.148 · Cited by 2

Image Retrieval Using Features From Pre-Trained Deep CNN

Bhandi, V., & Devi, K. A. S. (2020) · International journal of scientific and technology research · Cited by 2

A Transfer Learning Method for Deep Networks with Small Sample Sizes

Zheng, X. W., Lin, L., Liang, S., Rao, B., & Zhan, R. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1631/1/012072 · Cited by 2

Data Augmentation Guidelines for Cross-Dataset Transfer Learning and Pseudo Labeling

dos Santos, F. P., Thumé, G. S., & Ponti, M. A. (2021) · SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) · doi:10.1109/sibgrapi54419.2021.00036 · Cited by 2

Close-Grained Classification of Military Aircrafts

Patnaik, S., Kumar, A., Piyush, K., Katyayan, A., Sengupta, S., & Tripathy, S. (2022) · International Conference on Next Generation Intelligent Systems (ICNGIS) · doi:10.1109/icngis54955.2022.10079884 · Cited by 2

A Method to Improve the Performance of Network Data Analytics Function Based on Transfer Learning

Yu, M., Li, P., Xing, Y., & Liu, Y. (2023) · IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) · doi:10.1109/bmsb58369.2023.10211191 · Cited by 2

Adversarial Transform Networks for Unsupervised Transfer Learning

Cai, G., Wang, Y., He, L., & Zhou, M. (2020) · IEEE International Conference on Networking, Sensing and Control (ICNSC) · doi:10.1109/icnsc48988.2020.9238125 · Cited by 2

Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts

Nickchen, T., Heindorf, S., & Engels, G. (2021) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv48630.2021.00204 · Cited by 2

Features transfer learning for image and video recognition tasks

dos Santos, F. P., & Ponti, M. A. (2020) · SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) · doi:10.5753/sibgrapi.est.2020.12980 · Cited by 2

Deep Networks Based Classification of COVID-19 Chest X-Ray Images

Baseer, A., & Bhatti, N. (2020) · International Conference on Open Source Systems and Technologies (ICOSST) · doi:10.1109/icosst51357.2020.9333076 · Cited by 2

Common‐specific feature learning for multi‐source domain adaptation

Niu, C., Shang, J., Zhou, Z., Huang, J., Wang, T., & Li, X. (2020) · IET Image Processing · doi:10.1049/iet-ipr.2019.1712 · Cited by 2

Representation-Learning-Based Fusion Model for Scene Classification Using Convolutional Neural Network (CNN) and Pre-trained CNNs as Feature Extractors

Rukmangadha, P. V., & Das, R. K. K. (2021) · Advances in intelligent systems and computing · doi:10.1007/978-981-16-2543-5_54 · Cited by 2

Solving 2D Poisson's equation based on conditional generative adversarial network

Peng, K.-N., & Xu, F. Y. (2022) · International Journal of Numerical Modelling Electronic Networks Devices and Fields · doi:10.1002/jnm.3020 · Cited by 2

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 · Cited by 2

Transfer Learning, Cross Learning and Co-Learning Across Newsvendor Systems with Operational Data Analytics (ODA)Preprint

Feng, Q., Li, L., & Shanthikumar, J. G. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4629760 · Cited by 2

Domain adaptation of word embeddings through the exploitation of in-domain corpora and knowledge bases

Boukkouri, H. E. (2021) · theses.fr (ABES) · doi:10.70675/4c63eb46zd8cfz4a5dz80e9z666563e756d8 · Cited by 2

An Explainable Deep-Learning Model to Aid in the Diagnosis of Age Related Macular Degeneration

Herrero-Tudela, M., Romero-Oraá, R., Hornero, R., Gutiérrez‐Tobal, G. C., López, M. I., & García, M. (2024) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-031-61625-9_10 · Cited by 1

An Underwater Acoustic Target Recognition Method Based on Transfer Learning

Yang, X., Yu, H., Sheng, H., Zeng, W., He, Q., & Tu, J. (2024) · International Conference on Electronic Technology and Information Science (ICETIS) · doi:10.1109/icetis61828.2024.10593667 · Cited by 1

Fire and Smoke Detection Using Deep Learning

Pandey, S., Maurya, V. K., Patel, S., Mittal, S., & Sahu, S. (2024) · International Conference on Advanced Computing and Emerging Technologies (ACET) · doi:10.1109/acet61898.2024.10730263 · Cited by 1

A stacking ensemble method with multiple color models for lung cancer classification using histopathology images

Hazra, M., Gautam, N., Dey, J., & Sarkar, R. (2025) · Multimedia Tools and Applications · doi:10.1007/s11042-025-20942-8 · Cited by 1

Bridging data gaps for EV demand estimation: A transfer learning approach

Roozkhosh, F., Yao, X. A., Tahmasbi, B., Yang, H., & Mai, G. (2025) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2025.104539 · Cited by 1

An improved transfer learning for surface defect detection in edge-cloud continuum environments

Tang, B. T., Lin, Y., Cao, Y., Zhang, L., Ma, X., & Yang, Q. (2026) · The Journal of Supercomputing · doi:10.1007/s11227-025-07993-2 · Cited by 1

Artificial intelligence–Assisted tissue classification in Chironomus riparius : A potential tool for ecotoxicological studies

Stojanović, J., Milosavljević, A., Savić‐Zdravković, D., & Milošević, D. (2026) · Environmental Toxicology and Chemistry · doi:10.1093/etojnl/vgag059 · Cited by 1

Multitask and Transfer Learning of Geometric Robot Motion

Sugaya, S., Yousefi, M. R., Ferdinand, A. R., Morales, M., & Tapia, L. (2021) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros51168.2021.9636052 · Cited by 1

Malicious Family Identify Combining Multi-channel Mapping Feature Image and Fine-Tuned CNN

Tang, C., Zhou, C., Hu, M., Yang, M., & Qiang, B. (2022) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom56396.2022.00013 · Cited by 1

Restaurant and Café Menu Image Classification Based on Deep Neural Networks

Obaid, W., & Mansoor, W. (2024) · International Conference on Consumer Electronics · doi:10.1109/icce59016.2024.10444385 · Cited by 1

Deep Learning for Automatic Classification of Fruits and Vegetables: Evaluation from the Perspectives of Efficiency and Accuracy

Sönmez, D. P., & Kılıç, Ş. (2024) · Türkiye teknoloji ve uygulamalı bilimler dergisi. · doi:10.70562/tubid.1520357 · Cited by 1

Analyzing the impact of redaction on document classification performance of deep CNN models

Pagel, J., Vogl, S., & Israel, L. (2024) · International Journal on Document Analysis and Recognition (IJDAR) · doi:10.1007/s10032-024-00502-w · Cited by 1

A feasibility study of lung tumor segmentation on kilo-voltage radiographic images with transfer learning: Toward tumor motion tracking in radiotherapy

Wei, J., Deng, J., & Chao, M. (2025) · Physica Medica · doi:10.1016/j.ejmp.2025.104943 · Cited by 1

The Bright Side of the Moon: Transfer Learning and Creativity in Machine Learning Practice

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Rapid traceability of coffee bean by integrating an electronic tongue with knowledge distillation and transfer learning

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BCI-Based Cross-Dataset Mental Workload Assessment: Integrating Transfer Learning with XAI for EEG-Based Analysis

CHATURVEDI, S. K., & Ahirwal, M. K. (2025) · International Conference on Computational Intelligence and Communication Networks (CICN) · doi:10.1109/cicn67655.2025.11368246 · Cited by 1

Transfer Learning, Cross Learning and Co-Learning with Operational Data Analytics (ODA)

Feng, Q., Li, L. K., & Shanthikumar, J. G. (2026) · Management Science · doi:10.1287/mnsc.2023.03688 · Cited by 1

Transfer Learning for Collaborative Filtering Using a Psychometrics Model

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Online primal–dual learning for a data-dependent multi-kernel combination model with multiclass visual categorization applications

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Making the torch lighter: Areinforced active sampling framework for image classification

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Agent Simulation Model Based on Similarity Measure

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Thermal Face Detection for High-Speed AI Thermometer

Lee, W., Kwon, H., & Choi, J. (2021) · IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) · doi:10.1109/ic-nidc54101.2021.9660583 · Cited by 1

Mobile Food Journalling Application with Convolutional Neural Network and Transfer Learning: A Case for Diabetes Management in Malaysia

Chew, J. T., Sebastian, Y., Raman, V., & Then, P. (2022) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2022.0130986 · Cited by 1

Transfer Learning Realized With Nonlinearly Transformed Input Space

Zhu, X., Wang, D., Pedrycz, W., & Li, Z. (2022) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2022.3210568 · Cited by 1

Senegalese Fashion Apparels Classification System Using Deep Learning

Seck, A. C., Kaleemunnisa, F. N. U., Bathula, K. M., & Scharff, C. (2023) · Springer proceedings in complexity · doi:10.1007/978-3-031-19560-0_60 · Cited by 1

Active Selection Transfer Learning Algorithm

Wu, W., Zhang, Y., & Xing, F. (2023) · Neural Processing Letters · doi:10.1007/s11063-023-11240-1 · Cited by 1

A Collaborative Filtering Cross-Domain Recommendation Based on Matrix Blocking Technique

姜, 树. (2023) · Modeling and Simulation · doi:10.12677/mos.2023.123192 · Cited by 1

Imagelytics: A Deep Learning-Based Image Classification Tool to Support Bioassessment

Milosavljević, A., Predić, B., & Milošević, D. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-38616-9_5 · Cited by 1

An intensity-based deep approach to mitigate step-imbalance problem under extreme paucity of images from rare classes

Vemulapalli, V. M., Chakraborty, S., & Korra, S. B. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-19303-8 · Cited by 1

Inclusion Ethics in AI: Use Cases in African Fashion

Scharff, C., Brusseau, J., Bathula, K. M., Kaleemunnisa, F. N. U., Meshram, S. R., & Gaikhe, O. (2024) · Proceedings of the AAAI Symposium Series · doi:10.1609/aaaiss.v3i1.31266 · Cited by 1

Infrared Thermal Image Fault Detection of Electric Motor Based on Improved VGG16 Network Model

Zhu, X., Hu, S., Bing, Z., & Zhao, D. (2024) · International Conference on Communications, Information System and Computer Engineering (CISCE) · doi:10.1109/cisce62493.2024.10653406 · Cited by 1

Research and Implementation of Data Enhancement Techniques for Graph Neural Networks

Gu, J., & Huang, H. (2024) · International Conference on Artificial Intelligence and Electromechanical Automation (AIEA) · doi:10.1109/aiea62095.2024.10692981 · Cited by 1

IensNet: A novel and efficient approach for iris spoof detection via ensemble of deep models

Sharma, D., & Selwal, A. (2025) · Multimedia Tools and Applications · doi:10.1007/s11042-024-20524-0 · Cited by 1

Automated Visual Inspection for Defects Using Data Augmentation for Deep Learning-Based Image Classification

Ndukwe, I. K., & Boby, R. A. (2025) · Lecture notes in mechanical engineering · doi:10.1007/978-981-97-6176-0_17 · Cited by 1

Machine learning approaches for small data in sensor fusion applications

Verma, D. C., Bent, G. A., de Mel, G. R., & Simpkin, C. (2018) · Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR · doi:10.1117/12.2306041 · Cited by 1

Big Cities transfer learning

Diasse, A., & Li, Z. (2018) · International Conference on Machine Learning and Computing (ICMLC) · doi:10.1145/3195106.3195121 · Cited by 1

[Papers] Multi-classifier Decision: Integration of Multiple Brain Activity-based Classifications

Ogawa, T., Sugata, K., Togo, R., & Haseyama, M. (2018) · ITE Transactions on Media Technology and Applications · doi:10.3169/mta.7.36 · Cited by 1

Domain-invariant Adaptation Exploiting Statistical and Geometrical Properties

Azarkesht, M., & Afsari, F. (2019) · Iranian Joint Congress on Fuzzy and Intelligent Systems · doi:10.1109/cfis.2019.8692162 · Cited by 1

Initial investigation into the effect of image degradation on the performance of a 3-category classifier using transfer learning and data augmentation

Anthony, K., Borghetti, B. J., & Steward, B. J. (2019) · Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery · doi:10.1117/12.2519019 · Cited by 1

Terminal Bulb Segmentation of Caenorhabditis Elegans under Small Samples Based on Two-stage U-Net Network

Cao, S., & Liu, J. (2019) · doi:10.1145/3374587.3374624 · Cited by 1

MM-Net: Learning Adaptive Meta-metric for Few-Shot Biometric Recognition

Gu, Q., Luo, Z., Zhao, W., & Zhu, Y. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-67832-6_22 · Cited by 1

Light-weight MobileNet for Fast Detection of COVID-19

Firmansyah, M. H., Koh, S., Dewanto, W. K., & Puspitasari, T. D. (2021) · Jurnal Teknologi Informasi dan Terapan · doi:10.25047/jtit.v8i1.214 · Cited by 1

What Augmentations are Sensitive to Hyper-Parameters and Why?

Awais, C. M., Bekkouch, I. E. I., & Khan, A. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-031-10461-9_31 · Cited by 1

Handwritten Documents Validation Using Pattern Recognition and Transfer Learning

Jadli, A., Hain, M., & Chergui, A. (2021) · International Journal of Web-Based Learning and Teaching Technologies · doi:10.4018/ijwltt.20220901.oa1 · Cited by 2

Anomalous Activity Detection in Videos Using Increment Learning

Didwania, P., & Jagtap, V. S. (2020) · European Journal of Engineering and Technology Research · doi:10.24018/ejeng.2020.5.3.1803 · Cited by 1

Overview of Edge Intelligence and Blockchain

Wang, X., Qiu, C., Ren, X., Xiong, Z., Leung, V. C. M., & Niyato, D. T. (2022) · Wireless networks · doi:10.1007/978-3-031-10186-1_2 · Cited by 1

Data Augmentation Methods for Semantic Similarity Detection in Vietnamese Questionnaire

Anh, N. N. T., & Tran, T.-T. (2022) · RIVF International Conference on Computing and Communication Technologies (RIVF) · doi:10.1109/rivf55975.2022.10013827 · Cited by 1

Fast implementation of object detection algorithm based on homomorphic model transformation

Liu, J., & Zhang, H. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.127313 · Cited by 1

Anomalous Behaviour Detection using Heterogeneous Data

Ali, A. M. (2018) · Lancaster EPrints (Lancaster University) · doi:10.17635/lancaster/thesis/293 · Cited by 1

Machine learning based automated evaluation of piping design

Tan, W. C. (2019) · doi:10.32657/10220/48128 · Cited by 1

Cross-Domain Image Classification through Neural-Style Transfer Data AugmentationPreprint

Xu, Y., & Goel, A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.05611 · Cited by 1

Unsupervised Domain Expansion from Multiple SourcesPreprint

Zhang, J., Li, W., Sheng, L., Tang, C., & Ogunbona, P. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.12544 · Cited by 2

Explainable data fusion

Murray, B. (2021) · doi:10.32469/10355/85805 · Cited by 1

Classification and Prediction of Plant Diseases Based on AIPreprint

Krishna, D. P. B., GirijaRani, B., ChinaBabu, N., DevendarReddy, B., & SriTej, M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5048668 · Cited by 1

Visual recognition by learning from web data

Li, W. (2014) · doi:10.32657/10356/62186

Exponential Family Transfer Learning with Application to Text Document Modeling.

Rodrigues, R. N., & Govindaraju, V. (2017) · Proceeding Series of the Brazilian Society of Computational and Applied Mathematics · doi:10.5540/03.2017.005.01.0277

A Multiple Source based Transfer Learning Framework for Marketing Campaigns

Brownlow, J., Chu, C., Xu, G., Culbert, B., Fu, B., & Meng, Q. (2018) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2018.8489772

Fuzzy Domain Adaptation Using Unlabeled Target Data

Zuo, H., Zhang, G., & Jie Lu, B. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-04182-3_22

Humanoid Robot Detecting Animals via Neural Network

Yordanov, Y., & Mladenov, V. (2018) · Symposium on Neural Networks and Applications (NEUREL) · doi:10.1109/neurel.2018.8587017

Semi-Supervised Transfer Learning with Genetic Algorithm Tuned Transformation and Novel Label Transfer Mechanism

Salaken, S. M., Khosravi, A., Nguyen, T. T., & Nahavandi, S. (2018) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2018.00161

A Structural Retention Migration Affinity Propagation Algorithm

Xi, W., Chen, L., Ji, H., & Jun, Y. (2018) · IEEE International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) · doi:10.1109/auteee.2018.8720814

Transfer Learning for Cross-domain Visual Recognition

Zhang, J. (2019) · Research Online (University of Wollongong)

Deep multi-factor forensic face recognition

Ding (2018) · Digital Repository Service (Northeastern University) · doi:10.17760/d20292360

Graph Regularized Domain Adaptation for Cross Domain Image Recognition

Huang, J., Liu, K., Zhou, Z., & Chen, Z. (2019) · Chinese Control Conference (CCC) · doi:10.23919/chicc.2019.8866349

Classification of Cotton and Flax Fiber Images Based on Inductive Transfer Learning

Jiang, Y., Cai, S., Zeng, C., & Wang, Z. (2019) · Lecture notes in networks and systems · doi:10.1007/978-3-030-33506-9_79

Rozpoznawanie twarzy z wykorzystaniem technik głębokiego uczenia i fuzji danych obrazowych

Chmielińska, J. (2019) · PRZEGLĄD ELEKTROTECHNICZNY · doi:10.15199/48.2019.11.39

Deep Convolutional Neural Network Exploiting Transfer Learning for Country Recognition by Classifying Passport Cover

Hasan, M. J., Wahid, M. F., & Alom, M. S. (2019) · International Conference on Advances in Electrical Engineering · doi:10.1109/icaee48663.2019.8975666

Transfer Learning Model for Detecting Early Stage of Prurigo Nodularis

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Transfer learning for visual recognition and text categorization

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