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Deep Learning Model Compression for Resource Efficient Activity Recognition on Edge Devices: A Case Study.

, , , , , and . VISIGRAPP (4): VISAPP, page 575-584. SCITEPRESS, (2024)

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Deep Set Conditioned Latent Representations for Action Recognition., , , , , and . VISIGRAPP (5: VISAPP), page 456-466. SCITEPRESS, (2022)Interpreting Convolutional Neural Networks by Explaining Their Predictions., , and . ICIP, page 1685-1689. IEEE, (2023)AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence., , , , and . CIKM, page 5160. ACM, (2022)AIMLAI'20: Third Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence., , , , and . CIKM, page 3529-3530. ACM, (2020)Task Independent Capsule-Based Agents for Deep Q-Learning., , , , , and . BNAIC/BENELEARN, volume 1530 of Communications in Computer and Information Science, page 69-85. Springer, (2021)A Contrastive Learning Method for Multi-Label Predictors on Hyperspectral Images., and . WHISPERS, page 1-5. IEEE, (2023)MinMaxCAM: Improving object coverage for CAM-based Weakly Supervised Object Localization., , and . BMVC, page 238. BMVA Press, (2021)Recognizing Actions in High-Resolution Low-Framerate Videos: A Feasibility Study in the Construction Sector., , , and . VISIGRAPP (4): VISAPP, page 593-600. SCITEPRESS, (2024)Deep Learning Model Compression for Resource Efficient Activity Recognition on Edge Devices: A Case Study., , , , , and . VISIGRAPP (4): VISAPP, page 575-584. SCITEPRESS, (2024)Considering Layerwise Importance in the Lottery Ticket Hypothesis., and . CoRR, (2023)