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Review of lightweight deep convolutional neural networks
F Chen, S Li, J Han, F Ren, Z Yang - Archives of Computational Methods …, 2024 - Springer
Lightweight deep convolutional neural networks (LDCNNs) are vital components of mobile
intelligence, particularly in mobile vision. Although various heavy networks with increasingly …
intelligence, particularly in mobile vision. Although various heavy networks with increasingly …
On the use of deep learning for video classification
The video classification task has gained significant success in the recent years. Specifically,
the topic has gained more attention after the emergence of deep learning models as a …
the topic has gained more attention after the emergence of deep learning models as a …
X3d: Expanding architectures for efficient video recognition
This paper presents X3D, a family of efficient video networks that progressively expand a
tiny 2D image classification architecture along multiple network axes, in space, time, width …
tiny 2D image classification architecture along multiple network axes, in space, time, width …
Deep learning for diagnosis of COVID-19 using 3D CT scans
A new pneumonia-type coronavirus, COVID-19, recently emerged in Wuhan, China. COVID-
19 has subsequently infected many people and caused many deaths worldwide. Isolating …
19 has subsequently infected many people and caused many deaths worldwide. Isolating …
A comprehensive study of deep video action recognition
Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …
last decade, we have witnessed great advancements in video action recognition thanks to …
Patch-vq:'patching up'the video quality problem
No-reference (NR) perceptual video quality assessment (VQA) is a complex, unsolved, and
important problem for social and streaming media applications. Efficient and accurate video …
important problem for social and streaming media applications. Efficient and accurate video …
Dynamic hand gesture recognition based on short-term sampling neural networks
Hand gestures are a natural way for human-robot interaction. Vision based dynamic hand
gesture recognition has become a hot research topic due to its various applications. This …
gesture recognition has become a hot research topic due to its various applications. This …
You only watch once: A unified cnn architecture for real-time spatiotemporal action localization
Spatiotemporal action localization requires the incorporation of two sources of information
into the designed architecture:(1) temporal information from the previous frames and (2) …
into the designed architecture:(1) temporal information from the previous frames and (2) …
Frameexit: Conditional early exiting for efficient video recognition
In this paper, we propose a conditional early exiting framework for efficient video
recognition. While existing works focus on selecting a subset of salient frames to reduce the …
recognition. While existing works focus on selecting a subset of salient frames to reduce the …
DTCM: Joint optimization of dark enhancement and action recognition in videos
Recognizing human actions in dark videos is a useful yet challenging visual task in reality.
Existing augmentation-based methods separate action recognition and dark enhancement …
Existing augmentation-based methods separate action recognition and dark enhancement …