A Novel Method for Fashion Clothing Image Classification Based on Deep Learning

Abstract

Image recognition and classification is a significant research topic in computational vision and widely used computer technology. Themethods often used in image classification and recognition tasks are based on deep learning, like Convolutional Neural Networks(CNNs), LeNet, and Long Short-Term Memory networks (LSTM). Unfortunately, the classification accuracy of these methods isunsatisfactory. In recent years, using large-scale deep learning networks to achieve image recognition and classification canimprove classification accuracy, such as VGG16 and Residual Network (ResNet). However, due to the deep network hierarchyand complex parameter settings, these models take more time in the training phase, especially when the sample number is small, which can easily lead to overfitting. This paper suggested a deep learning-based image classification technique based on a CNN model and improved convolutional and pooling layers. Furthermore, the study adopted the approximate dynamic learning rate update algorithm in the model training to realize the learning rate’s self-adaptation, ensure the model’s rapid convergence, and shorten the training time. Using the proposed model, an experiment was conducted on the Fashion-MNIST dataset, taking 6,000 images as the training dataset and 1,000 images as the testing dataset. In actual experiments, the classification accuracy of the suggested method was 93 percent, 4.6 percent higher than that of the basic CNN model. Simultaneously, the study compared the influence of the batch size of model training on classification accuracy. Experimental outcomes showed this model is very generalized in fashion clothing image classification tasks.

Queens of the Digital Realm: Unveiling of Female Social Media through Personal Branding Analysis

“…The personality element Maria Rahajeng shows on Instagram as an influencer in the lifestyle category is that she is polite, caring about her family, and has good relationships with those closest to her. Apart from having a supportive personality towards those around her, Maria also shows a competitive character, which makes her open to new things and a perfectionist, as well as having a taste for classy and fashionable clothes since fashion clothing has always been important for people seeking to express their personal style and taste in life (Shin et al, 2023). Meanwhile, based on the personality elements shown by Tsamara Amany on Instagram indicate that Tsamara has an intelligent and broad-minded personality that makes her critical of current issues and willing to develop.…”

Optimizing the Architecture of Convolutional Neural Networks Using Modified Salp Swarm Algorithm

“…In [25] advantages established deep learning architectures like VGG16 and ResNet to achieve high classification accuracy. The authors further propose an approximate dynamic learning rate update algorithm to promote faster convergence and shorten training time.…”

“…Methods P-Value [14] PSO (DPSO) 0.008 [18] CAF 0.005 [23] MCNN15 0.003 [24] ANN and CNN 0.002 [25] Approximate dynamic learning rate Update algorithm, ResNet, and VGG16 0.001 [26] LACHS 0.001…”

Hyperparameter Optimization for Convolutional Neural Networks using the Salp Swarm Algorithm

“…In [28], the study employed large-scale deep learning networks such as VGG16 and ResNet to enhance classification accuracy and an approximate dynamic learning rate update algorithm to ensure rapid convergence and reduced training time.…”