A Transfer Learning-Based Fine Tuned VGG16 Model for PCOS Classification

S Srivastav, K Guleria, S Sharma - 2024 2nd International …, 2024 - ieeexplore.ieee.org
The most prevalent hormonal condition is polycystic ovarian syndrome (PCOS), which
occurs when the ovaries produce an excessive amount of small fluid-filled sacs known as …

A Fine-Tuned ResNet50 Model for Multiclass Cancer Prediction

S Srivastav, K Guleria, S Sharma - 2023 1st DMIHER …, 2023 - ieeexplore.ieee.org
Cancer has maintained its position as a leading contributor to mortality across the world. To
enhance treatment outcomes and elevate cancer survival rates, which exert significant …

Deep Learning-based Convolutional Neural Network Model for Hair Diseases Detection

S Srivastav, K Guleria, S Sharma - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Bleaching, dying, straightening, curling, and other chemical treatments for hair are becoming
increasingly common around the world as people's interest in hairstyles and hair colouring …

A Transfer Learning-based Pre-trained VGG16 Model for Skin Disease Classification

G Singh, K Guleria, S Sharma - 2023 IEEE 3rd Mysore Sub …, 2023 - ieeexplore.ieee.org
Skin disorders pose a significant global health risk, impacting millions of individuals and
placing a substantial burden on healthcare systems. The accuracy and speed of diagnosis …

Fine-Tuned Convolutional Neural Network Model for Rice Leaf Disease Prediction

G Singh, K Guleria, S Sharma - 2023 2nd International …, 2023 - ieeexplore.ieee.org
Rice stands as a crucial sustenance for the majority of the global population, underscoring
its cultivation's significance within agriculture. Nonetheless, the vitality of rice crops is …

A Hybrid Cuckoo Search-K-means Model for Enhanced Intrusion Detection in Internet of Things

MY Hassan, AH Najim, KA Al-Sharhanee, MN Kadhim… - 2024 - researchsquare.com
Integrating machine learning (ML) into intrusion detection systems (IDS) is considered an
important topic for preventing the spread of cyber threats. However, when it comes to …