Jianhua Zheng

Xin Li, Yeying Jin, Xin Jin et al.

This paper reviews the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images. This challenge received a wide range of impressive solutions, which are developed and evaluated using our collected real-world Raindrop Clarity dataset. Unlike existing deraining datasets, our Raindrop Clarity dataset is more diverse and challenging in degradation types and contents, which includes day raindrop-focused, day background-focused, night raindrop-focused, and night background-focused degradations. This dataset is divided into three subsets for competition: 14,139 images for training, 240 images for validation, and 731 images for testing. The primary objective of this challenge is to establish a new and powerful benchmark for the task of removing raindrops under varying lighting and focus conditions. There are a total of 361 participants in the competition, and 32 teams submitting valid solutions and fact sheets for the final testing phase. These submissions achieved state-of-the-art (SOTA) performance on the Raindrop Clarity dataset. The project can be found at https://lixinustc.github.io/CVPR-NTIRE2025-RainDrop-Competition.github.io/.

Xudong Li, Yang Hu, Jianhua Zheng et al.

Data-driven methods have made great progress in fault diagnosis, especially deep learning method. Deep learning is suitable for processing big data, and has a strong feature extraction ability to realize end-to-end fault diagnosis systems. However, designing neural network architecture requires rich professional knowledge and debugging experience, and a lot of experiments are needed to screen models and hyperparameters, increasing the difficulty of developing deep learning models. Frortunately, neural architecture search (NAS) is developing rapidly, and is becoming one of the next directions for deep learning. In this paper, we proposed a NAS method for fault diagnosis using reinforcement learning. A recurrent neural network is used as an agent to generate network architecture. The accuracy of the generated network on the validation dataset is fed back to the agent as a reward, and the parameters of the agent are updated through the strategy gradient algorithm. We use PHM 2009 Data Challenge gearbox dataset to prove the effectiveness of proposed method, and obtain state-of-the-art results compared with other artificial designed network structures. To author's best knowledge, it's the first time that NAS has been applied in fault diagnosis.

Shenghui Su, Jianhua Zheng, Shuwang Lu

This paper gives the definitions of an extra superincreasing sequence and an anomalous subset sum, and proposes a fast quantum-safe asymmetric cryptosystem called JUOAN2. The new cryptosystem is based on an additive multivariate permutation problem (AMPP) and an anomalous subset sum problem (ASSP) which parallel a multivariate polynomial problem and a shortest vector problem respectively, and composed of a key generator, an encryption algorithm, and a decryption algorithm. The authors analyze the security of the new cryptosystem against the Shamir minima accumulation point attack and the LLL lattice basis reduction attack, and prove it to be semantically secure (namely IND-CPA) on the assumption that AMPP and ASSP have no subexponential time solutions. Particularly, the analysis shows that the new cryptosystem has the potential to be resistant to quantum computing attack, and is especially suitable to the secret communication between two mobile terminals in maneuvering field operations under any weather. At last, an example explaining the correctness of the new cryptosystem is given.

Shenghui Su, Jianhua Zheng, Shuwang Lu et al.

Fraud (swindling money, property, or authority by fictionizing, counterfeiting, forging, or imitating things, or by feigning other persons privately) forms its threats against public security and network security. Anti-fraud is essentially the identification of a person or thing. In this paper, the authors first propose the concept of idology - a systematic and scientific study of identifications of persons and things, and give the definitions of a symmetric identity and an asymmetric identity. Discuss the converting symmetric identities (e.g., fingerprints) to asymmetric identities. Make a comparison between a symmetric identity and an asymmetric identity, and emphasize that symmetric identities cannot guard against inside jobs. Compare asymmetric RFIDs with BFIDs, and point out that a BFID is lightweight, economical, convenient, and environmentalistic, and more suitable for the anti-counterfeiting and source tracing of consumable merchandise such as foods, drugs, and cosmetics. The authors design the structure of a united verification platform for BFIDs and the composition of an identification system, and discuss the wide applications of BFIDs in public security and network security - antiterrorism and dynamic passwords for example.