9 citations · 22 across the 12 of their papers we have counts for
13 papers
Amplifying the imaging power of digital sky surveys with space telescopes data and generative AI
Sai Teja Erukude, Lior Shamir
While Digital sky surveys provide excellent throughput of image data and can cover a large footprint, their imaging power is normally inferior to that of space-based telescopes. Sp…
From ARIMA to Attention: Power Load Forecasting Using Temporal Deep Learning
Suhasnadh Reddy Veluru, Sai Teja Erukude, Viswa Chaitanya Marella
Accurate short-term power load forecasting is important to effectively manage, optimize, and ensure the robustness of modern power systems. This paper performs an empirical evaluat…
AI-Driven Cybersecurity Threats: A Survey of Emerging Risks and Defensive Strategies
Sai Teja Erukude, Viswa Chaitanya Marella, Suhasnadh Reddy Veluru
Artificial Intelligence's dual-use nature is revolutionizing the cybersecurity landscape, introducing new threats across four main categories: deepfakes and synthetic media, advers…
CornViT: A Multi-Stage Convolutional Vision Transformer Framework for Hierarchical Corn Kernel Analysis
Sai Teja Erukude, Jane Mascarenhas, Lior Shamir
Accurate grading of corn kernels is critical for seed certification, directional seeding, and breeding, yet it is still predominantly performed by manual inspection. This work intr…
FedOnco-Bench: A Reproducible Benchmark for Privacy-Aware Federated Tumor Segmentation with Synthetic CT Data
Viswa Chaitanya Marella, Suhasnadh Reddy Veluru, Sai Teja Erukude
Federated Learning (FL) allows multiple institutions to cooperatively train machine learning models while retaining sensitive data at the source, which has great utility in privacy…
Multimodal Detection of Fake Reviews using BERT and ResNet-50
Suhasnadh Reddy Veluru, Sai Teja Erukude, Viswa Chaitanya Marella
In the current digital commerce landscape, user-generated reviews play a critical role in shaping consumer behavior, product reputation, and platform credibility. However, the prol…
Explainable Deep Learning in Medical Imaging: Brain Tumor and Pneumonia Detection
Sai Teja Erukude, Viswa Chaitanya Marella, Suhasnadh Reddy Veluru
Deep Learning (DL) holds enormous potential for improving medical imaging diagnostics, yet the lack of interpretability in most models hampers clinical trust and adoption. This pap…
Wavelet-based GAN Fingerprint Detection using ResNet50
Sai Teja Erukude, Suhasnadh Reddy Veluru, Viswa Chaitanya Marella
Identifying images generated by Generative Adversarial Networks (GANs) has become a significant challenge in digital image forensics. This research presents a wavelet-based detecti…
Fourier-Based GAN Fingerprint Detection using ResNet50
Sai Teja Erukude, Viswa Chaitanya Marella, Suhasnadh Reddy Veluru
The rapid rise of photorealistic images produced from Generative Adversarial Networks (GANs) poses a serious challenge for image forensics and industrial systems requiring reliable…
Identifying bias in CNN image classification using image scrambling and transforms
Sai Teja Erukude
CNNs are now prevalent as the primary choice for most machine vision problems due to their superior rate of classification and the availability of user-friendly libraries. These ne…
Galaxy image simplification using Generative AI
Sai Teja Erukude, Lior Shamir
Modern digital sky surveys have been acquiring images of billions of galaxies. While these images often provide sufficient details to analyze the shape of the galaxies, accurate an…
Explainable identification of similarities between entities for discovery in large text
Akhil Joshi, Sai Teja Erukude, Lior Shamir
With the availability of virtually infinite number text documents in digital format, automatic comparison of textual data is essential for extracting meaningful insights that are d…
Identifying Bias in Deep Neural Networks Using Image Transforms
Sai Teja Erukude, Akhil Joshi, Lior Shamir
CNNs have become one of the most commonly used computational tool in the past two decades. One of the primary downsides of CNNs is that they work as a ``black box", where the user…