Pattathal V. Arun

36 papers C 6Journal 26Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DSFNet: Dual-stream spatial-spectral fusion network for hyperspectral anomaly detection. Digit. Signal Process. Li Wu, Mingtao You, Dong Zhao, Xingchen Xu, Yiming Yao, Pattathal V. Arun, Kuanhong Cheng, Pei Xiang
2025	J	`jnl`	CIGGAN: A Ground-Penetrating Radar Image Generation Method Based on Feature Fusion. IEEE Trans. Geosci. Remote. Sens. Haoxiang Tian, Xu Bai, Xuguang Zhu, Pattathal V. Arun, Jingxuan Mi, Dong Zhao
2025	J	`jnl`	Hyperspectral video object tracking with cross-modal spectral complementary and memory prompt network. Knowl. Based Syst. Wenhao Jiang, Dong Zhao, Chen Wang, Xin Yu, Pattathal V. Arun, Yuta Asano, Pei Xiang, Huixin Zhou
2025	J	`jnl`	SASU-Net: Hyperspectral video tracker based on spectral adaptive aggregation weighting and scale updating. Expert Syst. Appl. Dong Zhao, Haorui Zhang, Kunpeng Huang, Xuguang Zhu, Pattathal V. Arun, Wenhao Jiang, Shiyu Li, Xiaofang Pei, Huixin Zhou
2025	J	`jnl`	SRTE-Net: Spectral-Spatial Similarity Reduction and Reorganized Texture Encoding for Hyperspectral Video Tracking. IEEE Signal Process. Lett. Wenhao Jiang, Weixiang Zhong, Pattathal V. Arun, Pei Xiang, Dong Zhao
2025	J	`jnl`	Spatial Nonstationarity in DL-Based Crop Phenological Analysis. IEEE Geosci. Remote. Sens. Lett. Pattathal V. Arun, Kuldeep Chaurasia, Soorya Suresh, Arnon Karnieli
2024	C	`conf`	Open-Set Identification of Minerals From CRISM Hyperspectral Data. IGARSS Sandeepan Dhoundiyal, Moni Shankar Dey, Shashikant Singh, Pattathal V. Arun, Guneshwar Thangjam, Alok Porwal
2024	J	`jnl`	Reinforced deep learning approach for analyzing spaceborne-derived crop phenology. Int. J. Appl. Earth Obs. Geoinformation Pattathal V. Arun, Arnon Karnieli
2023	J	`jnl`	An ISAR and Visible Image Fusion Algorithm Based on Adaptive Guided Multi-Layer Side Window Box Filter Decomposition. Remote. Sens. Jiajia Zhang, Huan Li, Dong Zhao, Pattathal V. Arun, Wei Tan, Pei Xiang, Huixin Zhou, Jianling Hu, Juan Du
2023	J	`jnl`	DSP-Net: A Dynamic Spectral-Spatial Joint Perception Network for Hyperspectral Target Tracking. IEEE Geosci. Remote. Sens. Lett. Xuguang Zhu, Haorui Zhang, Bin Hu, Kunpeng Huang, Pattathal V. Arun, Xiuping Jia, Dong Zhao, Qing Wang, Huixin Zhou, Shuowen Yang
2023	C	`conf`	Graph Neural Network Based Interpretable Spectral Unmixing for Hyperspectral Unmixing Hyperspectral IIRS Data Onboard Chandrayaan-2 Mission. IGARSS Pattathal V. Arun, Maitreya Mohan Sahoo, Alok Porwal
2023	J	`jnl`	Hyperspectral Video Tracker Based on Spectral Deviation Reduction and a Double Siamese Network. Remote. Sens. Zhe Zhang, Bin Hu, Mengyuan Wang, Pattathal V. Arun, Dong Zhao, Xuguang Zhu, Jianling Hu, Huan Li, Huixin Zhou, Kun Qian
2023	J	`jnl`	Hyperspectral video target tracking based on pixel-wise spectral matching reduction and deep spectral cascading texture features. Signal Process. Dong Zhao, Xuguang Zhu, Zhe Zhang, Pattathal V. Arun, Jialu Cao, Qing Wang, Huixin Zhou, Hao Jiang, Jianling Hu, Kun Qian
2023	C	`conf`	Modeling Spectral Mixing for Geological Mixtures: Detecting Nonlinearly Mixed Pixels in Hyperspectral Image of Banded Hematite Quartzite. IGARSS Maitreya Mohan Sahoo, R. Kalimuthu, Pattathal V. Arun, Shibu K. Mathew, Alok Porwal
2023	J	`jnl`	Modelling Spectral Unmixing of Geological Mixtures: An Experimental Study Using Rock Samples. Remote. Sens. Maitreya Mohan Sahoo, R. Kalimuthu, Pattathal V. Arun, Alok Porwal, Shibu K. Mathew
2023	—	`conf`	Spectral Unmixing in Generative Space: 3D-GAN Based Approach. WHISPERS Soorya Suresh, Pattathal V. Arun, Alok Porwal
2022	J	`jnl`	Augmentation of Vegetation Index Curves Considering the Crop-Specific Phenological Characteristics. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Pattathal V. Arun, Arnon Karnieli
2022	J	`jnl`	Deep feature learning and latent space encoding for crop phenology analysis. Expert Syst. Appl. Pattathal V. Arun, Arnon Karnieli
2022	J	`jnl`	Hyperspectral Video Target Tracking Based on Deep Edge Convolution Feature and Improved Context Filter. Remote. Sens. Dong Zhao, Jialu Cao, Xuguang Zhu, Zhe Zhang, Pattathal V. Arun, Yecai Guo, Kun Qian, Like Zhang, Huixin Zhou, Jianling Hu
2022	J	`jnl`	Hyperspectral Video Target Tracking Based on Deep Features with Spectral Matching Reduction and Adaptive Scale 3D Hog Features. Remote. Sens. Zhe Zhang, Xuguang Zhu, Dong Zhao, Pattathal V. Arun, Huixin Zhou, Kun Qian, Jianling Hu
2022	J	`jnl`	Learning of physically significant features from earth observation data: an illustration for crop classification and irrigation scheme detection. Neural Comput. Appl. Pattathal V. Arun, Arnon Karnieli
2022	J	`jnl`	Multimodal Earth observation data fusion: Graph-based approach in shared latent space. Inf. Fusion Pattathal V. Arun, Roy Sadeh, Asaf Avneri, Yaniv Tubul, Carlos Camino, Krishna Mohan Buddhiraju, Alok Porwal, Ran Nisim Lati, Pablo J. Zarco-Tejada, Zvi Peleg, Ittai Herrmann
2021	J	`jnl`	Deep Learning-Based Phenological Event Modeling for Classification of Crops. Remote. Sens. Pattathal V. Arun, Arnon Karnieli
2021	—	`conf`	Support Vector Machines for Unmixing Geological Mixtures. WHISPERS Maitreya Mohan Sahoo, Pattathal V. Arun, Alok Porwal
2020	J	`jnl`	CNN based spectral super-resolution of remote sensing images. Signal Process. Pattathal V. Arun, Krishna Mohan Buddhiraju, Alok Porwal, Jocelyn Chanussot
2020	J	`jnl`	CNN-Based Super-Resolution of Hyperspectral Images. IEEE Trans. Geosci. Remote. Sens. Pattathal V. Arun, Krishna Mohan Buddhiraju, Alok Porwal, Jocelyn Chanussot
2019	J	`jnl`	Capsulenet-Based Spatial-Spectral Classifier for Hyperspectral Images. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Pattathal V. Arun, Krishna Mohan Buddhiraju, Alok Porwal
2019	J	`jnl`	Convolutional network architectures for super-resolution/sub-pixel mapping of drone-derived images. Pattern Recognit. Pattathal V. Arun, Ittai Herrmann, Krishna M. Budhiraju, Arnon Karnieli
2019	J	`jnl`	Spatial-spectral feature based approach towards convolutional sparse coding of hyperspectral images. Comput. Vis. Image Underst. Pattathal V. Arun, Krishna Mohan Buddhiraju, Alok Porwal
2018	—	`conf`	Analysis of capsulenets towards hyperspectral classification. WHISPERS Pattathal V. Arun, Krishna Mohan Buddhiraju, Alok Porwal
2018	J	`jnl`	CNN based sub-pixel mapping for hyperspectral images. Neurocomputing Pattathal V. Arun, Krishna Mohan Buddhiraju, Alok Porwal
2018	J	`jnl`	Integration of Contextual Knowledge in Unsupervised Subpixel Classification: Semivariogram and Pixel-Affinity Based Approaches. IEEE Geosci. Remote. Sens. Lett. Pattathal V. Arun, Krishna Mohan Buddhiraju, Alok Porwal
2018	C	`conf`	Inversion of Deep Networks for Modelling Variations in Spatial Distributions of Land Cover Classes Across Scales. IGARSS Pattathal V. Arun, Krishna Mohan Buddhiraju, Alok Porwal
2016	C	`conf`	A deep learning based spatial dependency modelling approach towards super-resolution. IGARSS Pattathal V. Arun, Krishna Mohan Buddhiraju
2016	C	`conf`	Classification and clustering perspective towards spectral unmxing. IGARSS Pattathal V. Arun, Krishna Mohan Buddhiraju
2016	—	`conf`	Integration of contextual knowledge in unsupervised sub-pixel classification. WHISPERS Pattathal V. Arun, Krishna Mohan Buddhiraju, Alok Porwal

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.