mobilenet3 [X:AI] MobileNet 논문 리뷰 논문 원본 : https://arxiv.org/abs/1704.04861 MobileNets: Efficient Convolutional Neural Networks for Mobile Vision ApplicationsWe present a class of efficient models called MobileNets for mobile and embedded vision applications. MobileNets are based on a streamlined architecture that uses depth-wise separable convolutions to build light weight deep neural networks. We introduce twarxiv.org Abstract.. 2025. 1. 12. [Paper Review] OverComing Oscillations in Quantization-Aware Training 논문 원본 : https://arxiv.org/abs/2203.11086 Overcoming Oscillations in Quantization-Aware TrainingWhen training neural networks with simulated quantization, we observe that quantized weights can, rather unexpectedly, oscillate between two grid-points. The importance of this effect and its impact on quantization-aware training (QAT) are not well-understarxiv.org Abstract딥러닝 모델을 simulated quantizati.. 2024. 11. 28. [X:AI] EfficientNet 논문 리뷰 EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks논문 원본 https://arxiv.org/abs/1905.11946발표 영상 https://www.youtube.com/watch?v=BfqNoIeNzyg&t=601s발표 자료 (오타 ICLR 2019 -> ICML 2019) EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksConvolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accu.. 2024. 4. 3. 이전 1 다음
