Learning Collision-Free Space Detection from Stereo Images: Homography Matrix Brings Better Data Augmentation

Collision-free space detection is a critical component of autonomous vehicle perception. The state-of-the-art algorithms are typically based on supervised learning. The performance of such approaches is always dependent on the quality and amount of labeled training data. Additionally, it remains an open challenge to train deep convolutional neural networks (DCNNs) using only a small quantity of training samples. Therefore, this paper mainly explores an effective training data augmentation approach that can be employed to improve the overall DCNN performance, when additional images captured from different views are available. Due to the fact that the pixels of the collision-free space (generally regarded as a planar surface) between two images captured from different views can be associated by a homography matrix, the scenario of the target image can be transformed into the reference view. This provides a simple but effective way of generating training data from additional multi-view images. Extensive experimental results, conducted with six state-of-the-art semantic segmentation DCNNs on three datasets, demonstrate the effectiveness of our proposed training data augmentation algorithm for enhancing collision-free space detection performance. When validated on the KITTI road benchmark, our approach provides the best results for stereo vision-based collision-free space detection.Comment: accepted to IEEE/ASME Transactions on Mechatronic

Frequent mutations of genes encoding ubiquitin-mediated proteolysis pathway components in clear cell renal cell carcinoma

We sequenced whole exomes of ten clear cell renal cell carcinomas (ccRCCs) and performed a screen of similar to 1,100 genes in 88 additional ccRCCs, from which we discovered 12 previously unidentified genes mutated at elevated frequencies in ccRCC. Notably, we detected frequent mutations in the ubiquitin-mediated proteolysis pathway (UMPP), and alterations in the UMPP were significantly associated with overexpression of HIF1 alpha and HIF2 alpha in the tumors (P = 0.01 and 0.04, respectively). Our findings highlight the potential contribution of UMPP to ccRCC tumorigenesis through the activation of the hypoxia regulatory network

Frequent mutations of chromatin remodeling genes in transitional cell carcinoma of the bladder

Transitional cell carcinoma (TCC) is the most common type of bladder cancer. Here we sequenced the exomes of nine individuals with TCC and screened all the somatically mutated genes in a prevalence set of 88 additional individuals with TCC with different tumor stages and grades. In our study, we discovered a variety of genes previously unknown to be mutated in TCC. Notably, we identified genetic aberrations of the chromatin remodeling genes (UTX, MLL-MLL3, CREBBP-EP300, NCOR1, ARID1A and CHD6) in 59% of our 97 subjects with TCC. Of these genes, we showed UTX to be altered substantially more frequently in tumors of low stages and grades, highlighting its potential role in the classification and diagnosis of bladder cancer. Our results provide an overview of the genetic basis of TCC and suggest that aberration of chromatin regulation might be a hallmark of bladder cancer