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Arijit Singha Hazari University of Stuttgart

Electrocatalytic proton reduction: Metal based fused diporphyrins with proton relays for efficient catalysis, , , , , , , , and . Dataset, (2024)Related to: Chandra, S., Singha Hazari, A., Song, Q., Hunger, D., Neuman, N. I., van Slageren, J., Klemm, E. & Sarkar, B. (2023). Remarkable Enhancement of Catalytic Activity of Cu-Complexes in the Electrochemical Hydrogen Evolution Reaction by Using Triply Fused Porphyrin. ChemSusChem 16, e202201146. doi: 10.1002/cssc.202201146.
 

Other publications of authors with the same name

Improving Recognition of Complex Aerial Scenes Using a Deep Weakly Supervised Learning Paradigm., and . IEEE Geosci. Remote. Sens. Lett., 15 (12): 1932-1936 (2018)QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results., , , , , , , , , and 82 other author(s). CoRR, (2021)Effective Building Extraction by Learning to Detect and Correct Erroneous Labels in Segmentation Mask., and . IGARSS, page 1288-1291. IEEE, (2018)Give me (un)certainty - An exploration of parameters that affect segmentation uncertainty., , , , and . CoRR, (2019)Federated Learning for Breast Density Classification: A Real-World Implementation., , , , , , , , , and 33 other author(s). DART/DCL@MICCAI, volume 12444 of Lecture Notes in Computer Science, page 181-191. Springer, (2020)Unsupervised Representation Learning by Predicting Image Rotations., , and . ICLR (Poster), OpenReview.net, (2018)Deep Tone Mapping Operator for High Dynamic Range Images., , , , , and . IEEE Trans. Image Processing, (2020)Deep Tone Mapping Operator for High Dynamic Range Images., , , , , and . CoRR, (2019)Autonomous robotic system for tunnel structural inspection and assessment., , , , , , , , , and 10 other author(s). IJIRA, 2 (1): 43-66 (2018)A Multilayer Markovian Model for Change Detection in Aerial Image Pairs with Large Time Differences., , and . ICPR, page 924-929. IEEE Computer Society, (2014)