Localization Recall Precision (LRP): A New Performance Metric for Object Detection

Average precision (AP), the area under the recall-precision (RP) curve, is the standard performance measure for object detection. Despite its wide acceptance, it has a number of shortcomings, the most important of which are (i) the inability to distinguish very different RP curves, and (ii) the lack of directly measuring bounding box localization accuracy. In this paper, we propose 'Localization Recall Precision (LRP) Error', a new metric which we specifically designed for object detection. LRP Error is composed of three components related to localization, false negative (FN) rate and false positive (FP) rate. Based on LRP, we introduce the 'Optimal LRP', the minimum achievable LRP error representing the best achievable configuration of the detector in terms of recall-precision and the tightness of the boxes. In contrast to AP, which considers precisions over the entire recall domain, Optimal LRP determines the 'best' confidence score threshold for a class, which balances the trade-off between localization and recall-precision. In our experiments, we show that, for state-of-the-art object (SOTA) detectors, Optimal LRP provides richer and more discriminative information than AP. We also demonstrate that the best confidence score thresholds vary significantly among classes and detectors. Moreover, we present LRP results of a simple online video object detector which uses a SOTA still image object detector and show that the class-specific optimized thresholds increase the accuracy against the common approach of using a general threshold for all classes. At https://github.com/cancam/LRP we provide the source code that can compute LRP for the PASCAL VOC and MSCOCO datasets. Our source code can easily be adapted to other datasets as well.Comment: to appear in ECCV 201

Luminescence emission from forward- and reverse-biased multicrystalline silicon solar cells

We study the emission of light from industrial multicrystalline silicon solar cells under forward and reverse biases. Camera-based luminescence imaging techniques and dark lock-in thermography are used to gain information about the spatial distribution and the energy dissipation at pre-breakdown sites frequently found in multicrystalline silicon solar cells. The pre-breakdown occurs at specific sites and is associated with an increase in temperature and the emission of visible light under reverse bias. Moreover, additional light emission is found in some regions in the subband-gap range between 1400 and 1700 nm under forward bias. Investigations of multicrystalline silicon solar cells with different interstitial oxygen concentrations and with an electron microscopic analysis suggest that the local light emission in these areas is directly related to clusters of oxygen. © 2009 American Institute of Physics

Localization recall precision (LRP): A new performance metric for object detection

Average precision (AP), the area under the recall-precision (RP) curve, is the standard performance measure for object detection. Despite its wide acceptance, it has a number of shortcomings, the most important of which are (i) the inability to distinguish very different RP curves, and (ii) the lack of directly measuring bounding box localization accuracy. In this paper, we propose “Localization Recall Precision (LRP) Error”, a new metric specifically designed for object detection. LRP Error is composed of three components related to localization, false negative (FN) rate and false positive (FP) rate. Based on LRP, we introduce the “Optimal LRP” (oLRP), the minimum achievable LRP error representing the best achievable configuration of the detector in terms of recall-precision and the tightness of the boxes. In contrast to AP, which considers precisions over the entire recall domain, oLRP determines the “best” confidence score threshold for a class, which balances the trade-off between localization and recall-precision. In our experiments, we show that oLRP provides richer and more discriminative information than AP. We also demonstrate that the best confidence score thresholds vary significantly among classes and detectors. Moreover, we present LRP results of a simple online video object detector and show that the class-specific optimized thresholds increase the accuracy against the common approach of using a general threshold for all classes. Our experiments demonstrate that LRP is more competent than AP in capturing the performance of detectors. Our source code for PASCAL VOC AND MSCOCO datasets are provided at https://github.com/cancam/LRP

The quest for companions to post-common envelope binaries. II. NSVS14256825 and HS0705+6700

We report new mid-eclipse times of the two close binaries NSVS14256825 and HS0705+6700, harboring an sdB primary and a low-mass main-sequence secondary. Both objects display clear variations in the measured orbital period, which can be explained by the action of a third object orbiting the binary. If this interpretation is correct, the third object in NSVS14256825 is a giant planet with a mass of roughly 12 M_Jup. For HS0705+6700, we provide evidence that strengthens the case for the suggested periodic nature of the eclipse time variation and reduces the uncertainties in the parameters of the brown dwarf implied by that model. The derived period is 8.4 yr and the mass is 31 M_Jup, if the orbit is coplanar with the binary. This research is part of the PlanetFinders project, an ongoing collaboration between professional astronomers and student groups at high schools.Comment: Accepted by Astron. and Astrophy

Multivariate analysis of 3D ToF-SIMS images: method validation and application to cultured neuronal networks

Advanced data analysis tools are crucial for the application of ToF-SIMS analysis to biological samples. Here, we demonstrate that by using a training set approach principal components analysis (PCA) can be performed on large 3D ToF-SIMS images of neuronal cell cultures. The method readily provides access to sample component information and significantly improves the images’ signal-to-noise ratio (SNR)

The DARS (Dopamine Augmented Rehabilitation in Stroke) trial: protocol for a randomised controlled trial of Co-careldopa treatment in addition to routine NHS occupational and physical therapy after stroke

Background: Stroke has a huge impact, leaving more than a third of affected people with lasting disability and rehabilitation remains a cornerstone treatment in the National Health Service (NHS). Recovery of mobility and arm function post-stroke occurs through re-learning to use the affected body parts and/or learning to compensate with the lesser affected side. Promising evidence suggests that the addition of Co-careldopa to physical therapy and occupational therapy may improve the recovery of arm and leg movement and lead to improved function. Methods/design: Dopamine Augmented Rehabilitation in Stroke (DARS) is a multi-centre double-blind, randomised, placebo, controlled clinical trial of Co-careldopa in addition to routine NHS occupational therapy and physical therapy as part of early stroke rehabilitation. Participants will be randomised on a 1:1 basis to either Co-careldopa or placebo. The primary objective of the trial is to determine whether the addition of six weeks of Co-careldopa treatment to rehabilitation therapy can improve the proportion of patients who can walk independently eight weeks post-randomisation. Discussion: The DARS trial will provide evidence as to whether Co-careldopa, in addition to routine NHS occupational and physical therapy, leads to a greater recovery of motor function, a reduction in carer dependency and advance rehabilitation treatments for people with stroke. Trial registration: ISRCTN99643613 assigned on 4 December 2009

Emotional Speech Perception Unfolding in Time: The Role of the Basal Ganglia

The basal ganglia (BG) have repeatedly been linked to emotional speech processing in studies involving patients with neurodegenerative and structural changes of the BG. However, the majority of previous studies did not consider that (i) emotional speech processing entails multiple processing steps, and the possibility that (ii) the BG may engage in one rather than the other of these processing steps. In the present study we investigate three different stages of emotional speech processing (emotional salience detection, meaning-related processing, and identification) in the same patient group to verify whether lesions to the BG affect these stages in a qualitatively different manner. Specifically, we explore early implicit emotional speech processing (probe verification) in an ERP experiment followed by an explicit behavioral emotional recognition task. In both experiments, participants listened to emotional sentences expressing one of four emotions (anger, fear, disgust, happiness) or neutral sentences. In line with previous evidence patients and healthy controls show differentiation of emotional and neutral sentences in the P200 component (emotional salience detection) and a following negative-going brain wave (meaning-related processing). However, the behavioral recognition (identification stage) of emotional sentences was impaired in BG patients, but not in healthy controls. The current data provide further support that the BG are involved in late, explicit rather than early emotional speech processing stages

Developing, monitoring, and reporting of fidelity in aphasia trials : core recommendations from the collaboration of aphasia trialists (CATs) trials for aphasia panel

BACKGROUND Developing, monitoring, and reporting of fidelity are essential and integral components to the design of randomised controlled trials (RCTs) in stroke and aphasia. Treatment fidelity refers to the degree to which an intervention is delivered as intended and is directly related to the quality of the evidence generated by RCTs. Clear documentation of treatment fidelity in trials assists in the evaluation of the clinical implications of potential benefits attributed to the intervention. Consideration of the implementation requirements of a research-based intervention as intended in a clinical context is necessary to achieve similar outcomes for a clinical population. Despite this, treatment fidelity is rarely reported in RCTs of aphasia intervention. AIM To describe fidelity strategies and develop core recommendations for developing, monitoring, and reporting of fidelity in aphasia intervention RCTs. SCOPE Relevant conceptual frameworks were considered. The Behaviour Change Consortium comprehensive framework of fidelity was adopted. It includes five areas: study design, training providers, delivery of treatment, treatment receipt, and treatment enactment. We explored fidelity in RCTs with a range of complex aphasia interventions (e.g., ASK, Big CACTUS, COMPARE, FCET2EC, POLAR, SUPERB, and VERSE) and described how different trial design factors (e.g., phase of trial, explanatory vs. pragmatic, number and location of sites, and number and type of treatment providers) influenced the fidelity strategies chosen. Strategies were mapped onto the five areas of the fidelity framework with a detailed exploration of how fidelity criteria were developed, measured, and monitored throughout each trial. This information was synthesised into a set of core recommendations to guide aphasia researchers towards the adequate measurement, capture, and reporting of fidelity within future aphasia intervention studies. CONCLUSIONS/RECOMMENDATIONS Treatment fidelity should be a core consideration in planning an intervention trial, a concept that goes beyond treatment adherence alone. A range of strategies should be selected depending on the phase and design of the trial being undertaken and appropriate investment of time and costs should be considered