Diffusion-Based Particle-DETR for BEV Perception

The Bird-Eye-View (BEV) is one of the most widely-used scene representations for visual perception in Autonomous Vehicles (AVs) due to its well suited compatibility to downstream tasks. For the enhanced safety of AVs, modeling perception uncertainty in BEV is crucial. Recent diffusion-based methods offer a promising approach to uncertainty modeling for visual perception but fail to effectively detect small objects in the large coverage of the BEV. Such degradation of performance can be attributed primarily to the specific network architectures and the matching strategy used when training. Here, we address this problem by combining the diffusion paradigm with current state-of-the-art 3D object detectors in BEV. We analyze the unique challenges of this approach, which do not exist with deterministic detectors, and present a simple technique based on object query interpolation that allows the model to learn positional dependencies even in the presence of the diffusion noise. Based on this, we present a diffusion-based DETR model for object detection that bears similarities to particle methods. Abundant experimentation on the NuScenes dataset shows equal or better performance for our generative approach, compared to deterministic state-of-the-art methods. Our source code will be made publicly available

Evaluation of Narrow-band imaging (NBI) with magnification colonoscopy for improving the diagnostic accuracy of the investigation

In last years many new endoscopic methods, as well as NBI have been introduced with aim to improve the diagnostic accuracy of colonoscopy. The data for their utility to be introduced in the routine clinical practice are not enough yet. The aim of this study was to evaluate the advantages of NBI with magnifying endoscopy compared to conventional colonoscopy for improving the diagnostic accuracy of endoscopic investigation. We analyzed the results of 330 patients with single or multiple (up to 5) colonic lesions found during standard colonoscopy (n=1530), and by magnifying NBI (n=2329Olympus Exera 180). With the use of magnifying endoscopy 799 new lesions were found, mainly benign lesions with size 5 mm (ð<0.001). Early cancer or high grade dysplasia was found in 4 new diagnosed lesions (total n=104), and low-grade - in 12 (total n=318). There was a significant correlation between the histological diagnosis and pit pattern of colonic mucosa according to the classification of S. Kudo et al. (ð<0.001), as well as the type of microvascular architecture, applying the classification of Y. Sano et al. (ð < 0.001). The diagnostic accuracy of NBI magnifying colonoscopy for prediction of the histological changes, evaluating the pit pattern type and type of capillary vessels was 92% and 96% for invasive adenocarcinoma, 95% and 87% - for early cancer or high-grade dysplasia, and between 95 - 100% - for benign lesions, respectively. In conclusion, NBI magnifying endoscopy is a promising method for the diagnosis of small colon lesions, especially for those with size less than 5 mm, and for the differentiation between neoplastic and non-neoplastic colon lesions, as well as the lesions with low-grade and high grade dyplasia or early colorectal carcinoma. In addition, it allows distinction of noninvasive from the invasive cancer

Towards Conscious RL Agents By Construction

The nature of consciousness has been a long-debated concept related to human cognition and self-understanding. As AI systems become more capable and autonomous, it is an increasingly pressing matter whether they can be called conscious. In line with narrative-based theories, here we present a simple but concrete computational criterion for consciousness grounded in the querying of a virtual self-representation. We adopt a reinforcement learning (RL) setting and implement these ideas in SubjectZero, a planning-based deep RL agent which has an explicit virtual self-model and whose architecture draws similarities to multiple prominent consciousness theories. Being able to self-localize, simulate the world, and model its own internal state, it can support a primitive virtual narrative, the quality of which depends on the number of abstractions that the underlying generative model sustains. Task performance still ultimately depends on the modeling capabilities of the agent where intelligence, understood simply as the ability to model complicated relationships, is what matters

Temperature limits during irradiation in laser-assisted treatment of peri-implantitis – laboratory research

Introduction: Peri-implantitis is a relatively new and difficult disease that is becoming more common. Of the different therapeutic options to manage this condition, lasers show certain advantages over other therapeutic alternatives because of their antibacterial potential. Aim: The aim of the present study was to investigate the temperature rise of implant surfaces, soft tissues, and bone during irradiation with diode, CO2, and Er:YAG lasers. Materials and methods: Ten implants inserted in biological models were irradiated with three laser systems with different parameters: a diode laser (980 nm) with power levels of 0.75 W and 1.6 W; a CO2 laser (10600 nm) with power levels of 252 W and 241 W; and an Er:YAG laser (2940 nm) with power levels of 1.5 W, 6.8 W, and 7.5 W. The temperature rise was measured using a specially designed thermal probe (type K thermocouple) with accuracy of ±0.1°C over the range from 20°C to 80°C. The temperature was measured at 5 points – in the implant body, in the mucosa, in the middle part of the implant, in the implant apex, and in the bone around the implant apex. Measurements were obtained at 1 minute working interval. Results: Diode and CO2 lasers with both parameters used increased significantly the temperature of more than 46°C, whereas the temperature in the Er:YAG laser group was less than 30°C. There was a statistically significant difference between diode, CO2, and Er:YAG lasers in favor of the erbium laser. Conclusions: The Er:YAG laser demonstrates the best thermal properties during irradiation of the implant surface. The three working modes tested – 1.5 W, 6.8 W, and 7.5 W – provide safe intervention on both the soft and bone tissues of the implant interface and on the implant itself