imjoel95.comSENet Paper ReviewSENet paper: https://arxiv.org/abs/1709.01507 The paper I'm going to read this time is SENet, Squeeze-and-Excitation Networks. SENet is a model that increases performance by focusing on interaction between channels. Interactions between channels can ...Nov 6, 2022·3 min read
imjoel95.comMobileNet V1MobileNet V1: https://arxiv.org/abs/1704.04861 In the early days of CNN, it is composed of a series of convolution-pooling, simply increasing the number of channels. The most intuitive structure is easy to understand and implement. However, the conv...Oct 30, 2022·2 min read
imjoel95.comResNet Paper ReviewResNet paper : https://arxiv.org/abs/1512.03385 Today, we're going to talk about ResNet, which was introduced by the Microsoft team in Deep Residual Learning for Image Recognition ResNet introduced a methodically novel concept rather than a mathemati...Oct 25, 2022·4 min read
imjoel95.comVGG paper reviewVGG paper : https://arxiv.org/abs/1409.1556 Abstarct The VGG paper investigates the accuracy pattern while increasing the depth of convolutional networts. The model is a 16-19 depth model using 3x3 convolution layers continuously. In fact, this model...Oct 18, 2022·3 min read
imjoel95.comYolo V3YOLO V3 paper : https://arxiv.org/abs/1804.02767?e05802c1_page=1 YOLOv3 is a lot like YOLOv2. I'm just going to write down the difference. 1. Abstract Updated from previous versions (YOLO v1, v2), YOLO v3 performs better than before. Increased accu...Oct 17, 2022·3 min read
