Adam, Hartwig

Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F., & Adam, H. (2018) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 20,063

Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F., & Adam, H. (2018) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 20,054

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Howard, A. G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., & Adam, H. (2017) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 19,015

Searching for MobileNetV3

Howard, A., Sandler, M., Chen, B., Wang, W., Chen, L.-C., Tan, M., Chu, G., Vasudevan, V., Zhu, Y., Pang, R., et al. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 9,708

Rethinking Atrous Convolution for Semantic Image Segmentation

Chen, L.-C., Papandreou, G., Schroff, F., & Adam, H. (2017) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 7,517

Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

Jacob, B., Kligys, S., Chen, B., Zhu, M., Tang, M., Howard, A., Adam, H., & Kalenichenko, D. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsLow-power high-performance VLSI design

Cited by 4,114

The iNaturalist Species Classification and Detection Dataset

Van Horn, G., Mac Aodha, O., Song, Y., Cui, Y., Sun, C., Shepard, A., Adam, H., Perona, P., & Belongie, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,451

Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation

Wang, H., Zhu, Y., Green, B., Adam, H., Yuille, A., & Chen, L.-C. (2020) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 809

Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation

Cheng, B., Collins, M. D., Zhu, Y., Liu, T., Huang, T. S., Adam, H., & Chen, L.-C. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 635

NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications

Yang, T.-J., Howard, A., Chen, B., Zhang, X., Go, A., Sandler, M., Sze, V., & Adam, H. (2018) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 572

FEELVOS: Fast End-To-End Embedding Learning for Video Object Segmentation

Voigtlaender, P., Chai, Y., Schroff, F., Adam, H., Leibe, B., & Chen, L.-C. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 468

Searching for Efficient Multi-Scale Architectures for Dense Image Prediction

Chen, L.-C., Collins, M. D., Zhu, Y., Papandreou, G., Zoph, B., Schroff, F., Adam, H., & Shlens, J. (2018) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 347

Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation

Chen, L.-C., Lopes, R. G., Cheng, B., Collins, M. D., Cubuk, E. D., Zoph, B., Adam, H., & Shlens, J. (2020) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 165

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69