AlignDet: Aligning Pre-training and Fine-tuning in Object Detection

The paradigm of large-scale pre-training followed by downstream fine-tuning has been widely employed in various object detection algorithms. In this paper, we reveal discrepancies in data, model, and task between the pre-training and fine-tuning procedure in existing practices, which implicitly limit the detector's performance, generalization ability, and convergence speed. To this end, we propose AlignDet, a unified pre-training framework that can be adapted to various existing detectors to alleviate the discrepancies. AlignDet decouples the pre-training process into two stages, i.e., image-domain and box-domain pre-training. The image-domain pre-training optimizes the detection backbone to capture holistic visual abstraction, and box-domain pre-training learns instance-level semantics and task-aware concepts to initialize the parts out of the backbone. By incorporating the self-supervised pre-trained backbones, we can pre-train all modules for various detectors in an unsupervised paradigm. As depicted in Figure 1, extensive experiments demonstrate that AlignDet can achieve significant improvements across diverse protocols, such as detection algorithm, model backbone, data setting, and training schedule. For example, AlignDet improves FCOS by 5.3 mAP, RetinaNet by 2.1 mAP, Faster R-CNN by 3.3 mAP, and DETR by 2.3 mAP under fewer epochs.Comment: Accepted by ICCV 2023. Code and Models are publicly available. Project Page: https://liming-ai.github.io/AlignDe

Preliminary investigation of the diagnosis and gene function of deep learning PTPN11 gene mutation syndrome deafness

Syndromic deafness caused by PTPN11 gene mutation has gradually come into the public’s view. In the past, many people did not understand its application mechanism and role and only focused on non-syndromic deafness, so the research on syndromic deafness is not in-depth and there is a large degree of lack of research in this area. In order to let the public know more about the diagnosis and gene function of deafness caused by PTPN11 gene mutation syndrome, this paper used deep learning technology to study the diagnosis and gene function of deafness caused by syndrome with the concept of intelligent medical treatment, and finally drew a feasible conclusion. This paper provided a theoretical and practical basis for the diagnosis of deafness caused by PTPN11 gene mutation syndrome and the study of gene function. This paper made a retrospective analysis of the clinical data of 85 deaf children who visited Hunan Children’s Hospital,P.R. China from January 2020 to December 2021. The conclusion were as follows: Children aged 1–6 years old had multiple syndrome deafness, while children under 1 year old and children aged 6–12 years old had relatively low probability of complex deafness; girls were not easy to have comprehensive deafness, but there was no specific basis to prove that the occurrence of comprehensive deafness was necessarily related to gender; the hearing loss of patients with Noonan Syndrome was mainly characterized by moderate and severe damage and abnormal inner ear and auditory nerve; most of the mutation genes in children were located in Exon1 and Exon3, with a total probability of 57.65%. In the course of the experiment, it was found that deep learning was effective in the diagnosis of deafness with PTPN11 gene mutation syndrome. This technology could be applied to medical diagnosis to facilitate the diagnosis and treatment of more patients with deafness with syndrome. Intelligent medical treatment was also becoming a hot topic nowadays. By using this concept to analyze and study the pathological characteristics of deafness caused by PTPN11 gene mutation syndrome, it not only promoted patients to find diseases in time, but also helped doctors to diagnose and treat such diseases, which was of great significance to patients and doctors. The study of PTPN11 gene mutation syndrome deafness was also of great significance in genetics. The analysis of its genes not only enriched the gene pool, but also provided reference for future research

Low-mass dark matter search results from full exposure of PandaX-I experiment

We report the results of a weakly-interacting massive particle (WIMP) dark matter search using the full 80.1\;live-day exposure of the first stage of the PandaX experiment (PandaX-I) located in the China Jin-Ping Underground Laboratory. The PandaX-I detector has been optimized for detecting low-mass WIMPs, achieving a photon detection efficiency of 9.6\%. With a fiducial liquid xenon target mass of 54.0\,kg, no significant excess event were found above the expected background. A profile likelihood analysis confirms our earlier finding that the PandaX-I data disfavor all positive low-mass WIMP signals reported in the literature under standard assumptions. A stringent bound on the low mass WIMP is set at WIMP mass below 10\,GeV/c$^2$, demonstrating that liquid xenon detectors can be competitive for low-mass WIMP searches.Comment: v3 as accepted by PRD. Minor update in the text in response to referee comments. Separating Fig. 11(a) and (b) into Fig. 11 and Fig. 12. Legend tweak in Fig. 9(b) and 9(c) as suggested by referee, as well as a missing legend for CRESST-II legend in Fig. 12 (now Fig. 13). Same version as submitted to PR

Early lineage restriction in temporally distinct populations of Mesp1 progenitors during mammalian heart development.

Cardiac development arises from two sources of mesoderm progenitors, the first heart field (FHF) and the second (SHF). Mesp1 has been proposed to mark the most primitive multipotent cardiac progenitors common for both heart fields. Here, using clonal analysis of the earliest prospective cardiovascular progenitors in a temporally controlled manner during early gastrulation, we found that Mesp1 progenitors consist of two temporally distinct pools of progenitors restricted to either the FHF or the SHF. FHF progenitors were unipotent, whereas SHF progenitors were either unipotent or bipotent. Microarray and single-cell PCR with reverse transcription analysis of Mesp1 progenitors revealed the existence of molecularly distinct populations of Mesp1 progenitors, consistent with their lineage and regional contribution. Together, these results provide evidence that heart development arises from distinct populations of unipotent and bipotent cardiac progenitors that independently express Mesp1 at different time points during their specification, revealing that the regional segregation and lineage restriction of cardiac progenitors occur very early during gastrulation.This is the author's accepted manuscript and will be under embargo until the 24th of February 2015. The final version is published by NPG in Nature Cell Biology here: http://www.nature.com/ncb/journal/v16/n9/full/ncb3024.html

Advances in the research of warship structural damage due to inner explosion

Anti-ship missile is the main threat to warship survivability. Having scientific understanding to the complex damage elements and its damage process when missile explosion occurred inner cabin is the important premise to warship protection structure design. But so far the researches on quantitative description of damage elements including explosion shock wave, fragments and explosive products, and damage mechanism and quantitative characterization of warship hull under those damage loading is far from adequate. On the basis of reviewing the achievements on the field that warship hull subjected to missile warhead inner explosion in recent years, the loading characteristic of damage elements were analyzed, and then specially focused on the main damage processes, research achievements in theory, simulation and experimentation were summarized. Some adequate in basic research was present in the end and some suggestion was put forward, which can provided useful reference to the design and related research on warship protection structures