Notice Board :





Volume XVI Issue XI

Author Name
Pratik Buchke, Aditi Sahu, Akanksha Thakre, Ayushi Soni, Ganesh Mishra
Year Of Publication
2024
Volume and Issue
Volume 16 Issue 11
Abstract
This paper explores the role of technical education in rural development, particularly focusing on Information Technology (IT) as a key enabler. It examines the disparities in IT access between rural and urban areas, the impact of IT training on employment, and the contributions of IT in agricultural development. Data collected from rural areas reveals significant gaps in internet penetration, access to IT education, and employment opportunities compared to urban regions. Additionally, the paper highlights the positive impact of IT applications on agricultural productivity, market access, and revenue generation. The study concludes that targeted IT education and infrastructure development are crucial for bridging the digital divide in rural areas. Recommendations include expanding mobile-based learning platforms, establishing community IT centers, and investing in specialized IT training programs for rural populations.
PaperID
2024/EUSRM/11/2024/61622

Author Name
Abhishek Shrivastava, Vivek Gautam, Naman Patel, Sunidhi Sharma, Mohit Kadwal
Year Of Publication
2024
Volume and Issue
Volume 16 Issue 11
Abstract
The popularity of anime as a unique and well-established art form, recognized worldwide has given a great boost to its automatic generation using machine learning. High-quality image synthesis recently became possible using GANs, which constituted an important device in its synthesis. Recent advances enable the generation of anime-inspired images with a close resemblance to reality regarding their style. Our proposed approach, PixelSake, adopts the architectural changes in both generator and discriminator combined to enhance anime-specific features using domain adaptation techniques that better capture the subtle nature of anime aesthetic. PixelSake integrates a multi-scale discriminator with feature-extracting generators for payoffs on anime-specific features, such as line art and color palettes, and exaggerated expressions, which are concentrated less on traditional GANs. The perceptual loss function with features of pre-trained neural networks has been used to improve the quality of
PaperID
2024/EUSRM/11/2024/61623