Table 1: Minimum Admission Criteria for Higher Degrees by ResearchĬompletion of research project in a related area including a thesis which is equivalent to at least 25% of a year’s full-time study at Level 8 or 9 of the Australian Qualifications Framework with achievement of a grade for the project equivalent to a Deakin grade of 70% or equivalent. (9) Additional eligibility for HDR scholarships is set out in the Higher Degrees by Research (HDR) Scholarships procedure. Additional evidence may include but is not limited to: workplace experience, verified reports, reviews, conference presentations, publications and data analysis. Where qualifications do not meet this requirement, the applicant must provide an additional portfolio of evidence of equivalent research or professional experience and outputs from the last five years to demonstrate, in the University’s judgement, that they are sufficiently prepared for HDR candidature.

(8) Relevant qualifications must have been obtained less than five years prior to application. (7) The applicant must provide evidence that they meet the minimum entry criteria outlined in Table 1 or establish to the satisfaction of the Deputy Vice-Chancellor Research or nominee that they have equivalent research experience with outputs that is sufficient to prepare them for HDR candidature. Course admission criteria specified in Table 1: Minimum Admission Criteria for Higher Degrees by Research.English language proficiency as specified in the Admission Minimum Eligibility Criteria procedure or other language proficiency approved by the Academic Board and.(6) To be considered for selection into an HDR course, the applicant must meet the following minimum admission criteria: (5) Prospective students will follow the application processes for HDR courses stipulated by the Graduate Research Academy. (4) This Procedure is pursuant to the Higher Degrees by Research (HDR) policy. It does not apply to undergraduate and postgraduate coursework programs or higher doctoral degrees. (3) This Procedure applies to the University’s HDR courses. (2) This Procedure documents the minimum criteria and processes for admission, selection and enrolment of applicants into the University’s higher degrees by research (HDR) courses. (1) This Procedure is effective from 25 November 2021. To view historic versions, click the link in the document's navigation bar. Durand acknowledges a Microsoft Research New Faculty Fellowship and a Sloan Fellowship.This is the current version of this document. This work was supported in part by an NSERC Postdoctoral Fellowship, NSF CAREER award 0447561, the Quanta T-Party, NGA NEGI-04, MURI Grant N0-0734, andį. densely sampled 'ground truth' sequence.highlights saturate in 1/800s at ISO 100.same time budget and #photos as exposure bracketing.LDR images saturate at 15280 (may seem underexposed in 16-bit format).noise and dynamic range of Canon EOS 1D Mark III simulated.highlights assumed to saturate in 1/100s at ISO 100.source HDR photo courtesy Rafał Mantiuk.Invited tutorial at ICCP 2010, Fundamentals of Computational Photography: Sensors and Noise.Extension with dark current noise, discussion of high vs.This advantage for both real and synthetic scenes. In the darkest regions), or much faster capture for the Same capture time (for some cameras, up to 19 dB improvement Our method lets us achieve higher worst-case SNR in the Of noise, we show that optimal capture can be formulated ISO settings, and spends disproportionately longer capturing Performance, in general, uses much higher and variable We show that the capture sequence with optimal worst-case Set of photos with geometrically-spaced exposure times, atĪ fixed ISO setting (typically ISO 100 or 200). To capture? The typical approach to HDR capture uses a Taking multiple exposures is a well-established approachīoth for capturing high dynamic range (HDR) scenes andįor noise reduction. 23rd IEEE Conference on Computer Vision and Pattern Recognition, Noise-Optimal Capture for High Dynamic Range Photography. Noise-Optimal Capture for High Dynamic Range Photography (Project) Noise-Optimal Capture for High Dynamic Range Photography Samuel W.

Hdr projects 2 vs 3